The data decontamination includes two steps: 1. species occupancy detection modeling 2. Bray-Curtis dissimilarity analysis

Here, I’ll read in the data from the SODM analysis, assess which ASVs will be removed based on that, and then move onto calculating the Bray-Curtis dissimilarities across sample replicates. Finally, the repicates that are more dissimilar (> 0.49) than similar to one another will be removed.

Load data and libraries

library(tidyverse)
library(stringi)
library(vegan)
library(reshape2)
library(textshape)
library(rlist)

As I did with the reference mock communities, the way I’m thinking about this is to create a .txt file with a list of the file names and loci and to read that in, but ideally, I would also have a column for the sample name so that I could actually properly filter for each locus-sample when anti-joining with the dataframe.

Before getting into all of that regex stuff, probably best to take a quick look at whether there are many ASVs that get removed for the data from F1 or the mock feed pools.

# Full dataframe
features_w_taxonomy <- readRDS("../data/feature_df_no_eDNA_metazoa_only.rds")

# and newly updated, the same dataframes, but using a 98% identity threshold for any species-level assignments
tax_df_spp_98 <- readRDS("../data/uncollapsed_taxonomy_spp_98.rds")
unique_tax_spp_98 <- readRDS("../data/unique_taxonomy_spp_98.rds")


# meta data for group and type assignments
meta <- read_csv("../data/jan_sample_list.csv")
Parsed with column specification:
cols(
  sample = col_character(),
  new_name = col_character(),
  type = col_character(),
  group = col_character(),
  filler = col_character(),
  perc_fishmeal = col_double()
)
# use the new name column to bind to the input file
feature_tax_name_revised <- features_w_taxonomy %>%
  left_join(., meta, by = "sample") %>%
  select(locus, seq, new_name, count) %>%
  rename(sample = new_name)

Occupancy modeling data

Based on the SODM filtering, now I need to read those data back in for the mock feed data/mixtures and pools.

The files are located in this directory: /Users/dianabaetscher/Documents/git-repos/metabarcoding-methods/Rmd_fixed_db/csv_outputs/SODM

# get the names of the files
fdf <- read.table("~/Documents/git-repos/metabarcoding-methods/data/sodm_samples_loc.txt", stringsAsFactors = FALSE, header = TRUE) %>%
  tbl_df()
dir <- "~/Documents/git-repos/metabarcoding-methods/Rmd_fixed_db/csv_outputs/SODM"

# cycle over them, read them and add the locus column on each.
# at the end, bind them together.
mock_feed_sodm_df <- lapply(1:nrow(fdf), function(i) {
  read_csv(paste(dir, fdf$file[i], sep = "/"), col_names = TRUE) %>%
    mutate(locus = fdf$locus[i]) %>%
    mutate(sample = fdf$sample[i]) %>%
    select(locus, sample, everything())
}) %>%
  bind_rows() %>%
  group_by(locus, sample, seq) %>%
  mutate(max_estimate = sum(estimate,std.error)) %>%
  mutate(max_estimate = ifelse(max_estimate > 1, 1, max_estimate)) %>% # make 1 the maximum probability.
  select(locus, seq, estimate, std.error, max_estimate)
Parsed with column specification:
cols(
  term = col_character(),
  estimate = col_double(),
  std.error = col_double(),
  seq = col_character()
)
Parsed with column specification:
cols(
  term = col_character(),
  estimate = col_double(),
  std.error = col_double(),
  seq = col_character()
)
Parsed with column specification:
cols(
  term = col_character(),
  estimate = col_double(),
  std.error = col_double(),
  seq = col_character()
)
Parsed with column specification:
cols(
  term = col_character(),
  estimate = col_double(),
  std.error = col_double(),
  seq = col_character()
)
Parsed with column specification:
cols(
  term = col_character(),
  estimate = col_double(),
  std.error = col_double(),
  seq = col_character()
)
Parsed with column specification:
cols(
  term = col_character(),
  estimate = col_double(),
  std.error = col_double(),
  seq = col_character()
)
Parsed with column specification:
cols(
  term = col_character(),
  estimate = col_double(),
  std.error = col_double(),
  seq = col_character()
)
Parsed with column specification:
cols(
  term = col_character(),
  estimate = col_double(),
  std.error = col_double(),
  seq = col_character()
)
Parsed with column specification:
cols(
  term = col_character(),
  estimate = col_double(),
  std.error = col_double(),
  seq = col_character()
)
Parsed with column specification:
cols(
  term = col_character(),
  estimate = col_double(),
  std.error = col_double(),
  seq = col_character()
)
Parsed with column specification:
cols(
  term = col_character(),
  estimate = col_double(),
  std.error = col_double(),
  seq = col_character()
)
Parsed with column specification:
cols(
  term = col_character(),
  estimate = col_double(),
  std.error = col_double(),
  seq = col_character()
)
Parsed with column specification:
cols(
  term = col_character(),
  estimate = col_double(),
  std.error = col_double(),
  seq = col_character()
)
Parsed with column specification:
cols(
  term = col_character(),
  estimate = col_double(),
  std.error = col_double(),
  seq = col_character()
)
Parsed with column specification:
cols(
  term = col_character(),
  estimate = col_double(),
  std.error = col_double(),
  seq = col_character()
)
Parsed with column specification:
cols(
  term = col_character(),
  estimate = col_double(),
  std.error = col_double(),
  seq = col_character()
)
Parsed with column specification:
cols(
  term = col_character(),
  estimate = col_double(),
  std.error = col_double(),
  seq = col_character()
)
Parsed with column specification:
cols(
  term = col_character(),
  estimate = col_double(),
  std.error = col_double(),
  seq = col_character()
)
Parsed with column specification:
cols(
  term = col_character(),
  estimate = col_double(),
  std.error = col_double(),
  seq = col_character()
)
Parsed with column specification:
cols(
  term = col_character(),
  estimate = col_double(),
  std.error = col_double(),
  seq = col_character()
)
Parsed with column specification:
cols(
  term = col_character(),
  estimate = col_double(),
  std.error = col_double(),
  seq = col_character()
)
Parsed with column specification:
cols(
  term = col_character(),
  estimate = col_double(),
  std.error = col_double(),
  seq = col_character()
)
Parsed with column specification:
cols(
  term = col_character(),
  estimate = col_double(),
  std.error = col_double(),
  seq = col_character()
)
Parsed with column specification:
cols(
  term = col_character(),
  estimate = col_double(),
  std.error = col_double(),
  seq = col_character()
)
Parsed with column specification:
cols(
  term = col_character(),
  estimate = col_double(),
  std.error = col_double(),
  seq = col_character()
)
Parsed with column specification:
cols(
  term = col_character(),
  estimate = col_double(),
  std.error = col_double(),
  seq = col_character()
)
Parsed with column specification:
cols(
  term = col_character(),
  estimate = col_double(),
  std.error = col_double(),
  seq = col_character()
)
Parsed with column specification:
cols(
  term = col_character(),
  estimate = col_double(),
  std.error = col_double(),
  seq = col_character()
)
Parsed with column specification:
cols(
  term = col_character(),
  estimate = col_double(),
  std.error = col_double(),
  seq = col_character()
)
Parsed with column specification:
cols(
  term = col_character(),
  estimate = col_double(),
  std.error = col_double(),
  seq = col_character()
)
Parsed with column specification:
cols(
  term = col_character(),
  estimate = col_double(),
  std.error = col_double(),
  seq = col_character()
)
Parsed with column specification:
cols(
  term = col_character(),
  estimate = col_double(),
  std.error = col_double(),
  seq = col_character()
)
Parsed with column specification:
cols(
  term = col_character(),
  estimate = col_double(),
  std.error = col_double(),
  seq = col_character()
)
Parsed with column specification:
cols(
  term = col_character(),
  estimate = col_double(),
  std.error = col_double(),
  seq = col_character()
)
Parsed with column specification:
cols(
  term = col_character(),
  estimate = col_double(),
  std.error = col_double(),
  seq = col_character()
)
Parsed with column specification:
cols(
  term = col_character(),
  estimate = col_double(),
  std.error = col_double(),
  seq = col_character()
)
Adding missing grouping variables: `sample`

So these are the ASVs that I would be filtering

mock_feed_sodm_asvs_removed <- mock_feed_sodm_df %>%
  filter(max_estimate < 0.8)

mock_feed_sodm_asvs_removed

There aren’t very many of these, but some…

so for consistency sake, I suppose better to remove them.

Anti-join the ASVs to remove with the full dataframe

mock_feed_feature_df <- feature_tax_name_revised %>%
  filter(!str_detect(sample, "VRP") & !str_detect(sample, "FRP") & !str_detect(sample, "extr_blank")) %>%
  separate(sample, into = c("filler", "perc_fishmeal", "extract", "pcr_rep"), sep = "_", remove = FALSE) %>%
  unite(feed, filler, perc_fishmeal, sep = "_", remove = TRUE) %>%
  select(-extract, -pcr_rep) %>%
  mutate(feed = ifelse(str_detect(feed, "MFP"), "MFP", feed)) %>%
  mutate(feed = ifelse(str_detect(feed, "MEP"), "MEP", feed))
Expected 4 pieces. Missing pieces filled with `NA` in 15887 rows [29386, 29387, 29388, 29389, 29390, 29391, 29392, 29393, 29394, 29395, 29396, 29397, 29398, 29399, 29400, 29401, 29402, 29403, 29404, 29405, ...].
# check that all of those modifications took effect - basically to make a column that I can use for an anti-join with the SODM filtered data
mock_feed_feature_df %>%
  filter(str_detect(sample, "MFP"))

Use an anti-join to remove the 27 ASVs from the full feature table.

mock_feed_sodm_asvs_removed_dataframe <- mock_feed_feature_df %>%
  anti_join(., mock_feed_sodm_asvs_removed, by = c("locus", "seq", "feed" = "sample")) %>%
  select(-feed) # remove the column that I used for the join since I don't need it moving forward

Save the output

saveRDS(mock_feed_sodm_asvs_removed_dataframe, "../data/mockfeed_sodm_asvs_removed_feature_df.rds", compress = "xz")

Dissimilarity analyses

Using the dataframe generated above…

Dissimilarity analyses include a PERMANOVA on Bray-Curtis Jaccard similarities (minimizing the effect of PCR amplification bias)

The process for looking at the dissimilarity among replicates is to: 1. read in data that has been cleaned up using the occupancy modeling 2. create a community matrix (per locus) 3. standardize data across replicates (fct decostand) 4. generate Bray-Curtis distances (fct vegdist) 4a. Are any replicates more dissimilar than similar? 5. generate NMDS plots from distance matrix (fct metaMDS)

Outcomes: Based on the NMDS plots and Bray-Curtis dissimilarity index, I will generate a list of samples to remove.

source("../R/metabarcoding-funcs.R")

Cycle over a list of the loci

# grab the names of the loci from the full dataframe
locs <- c("cep", "mifish", "nsCOIFo", "fishminiA")

# how many feed samples?
mock_feed_sodm_asvs_removed_dataframe %>%
  select(sample) %>%
  unique()
NA

NOTE: MEP and MFP have a diff number of parts than the mock feeds… 9 replicates vs. 6 replicates, so splitting the sample into reference, pool, and pcr replicate will look different.

Bray-Curtis function

Output from the function should go into a directory called csv_outputs/bray_dissimilar/mockfeeds/

If this directory doesn’t exist, the function will create it.

bray_nmds_mock_feed(mock_feed_sodm_asvs_removed_dataframe, loc = "cep", site = "F1_0")
'csv_outputs/bray_dissimilar/mockfeeds' already exists'nperm' >= set of all permutations: complete enumeration.
Set of permutations < 'minperm'. Generating entire set.
Run 0 stress 0 
Run 1 stress 0 
... Procrustes: rmse 0.08306481  max resid 0.1500837 
Run 2 stress 8.393474e-05 
... Procrustes: rmse 0.0650365  max resid 0.1016619 
Run 3 stress 9.601771e-05 
... Procrustes: rmse 0.1508988  max resid 0.2618136 
Run 4 stress 0 
... Procrustes: rmse 0.09565963  max resid 0.1719531 
Run 5 stress 9.762288e-05 
... Procrustes: rmse 0.1508948  max resid 0.2618009 
Run 6 stress 0 
... Procrustes: rmse 0.05516981  max resid 0.08298733 
Run 7 stress 0.005052253 
Run 8 stress 9.545577e-05 
... Procrustes: rmse 0.1508969  max resid 0.2618038 
Run 9 stress 6.304464e-05 
... Procrustes: rmse 0.06759018  max resid 0.1260851 
Run 10 stress 0 
... Procrustes: rmse 0.06590909  max resid 0.1190405 
Run 11 stress 3.912468e-05 
... Procrustes: rmse 0.07810179  max resid 0.1189405 
Run 12 stress 0.1964001 
Run 13 stress 0 
... Procrustes: rmse 0.05915666  max resid 0.1147621 
Run 14 stress 1.210162e-05 
... Procrustes: rmse 0.1275159  max resid 0.2214862 
Run 15 stress 0.1964001 
Run 16 stress 7.15227e-05 
... Procrustes: rmse 0.06823941  max resid 0.09896617 
Run 17 stress 7.930743e-05 
... Procrustes: rmse 0.1418135  max resid 0.2454811 
Run 18 stress 0.2181459 
Run 19 stress 0.004773638 
Run 20 stress 0 
... Procrustes: rmse 0.05536676  max resid 0.1114028 
Run 21 stress 0 
... Procrustes: rmse 0.05288896  max resid 0.07930563 
Run 22 stress 0 
... Procrustes: rmse 0.07216272  max resid 0.1259475 
Run 23 stress 0 
... Procrustes: rmse 0.09203779  max resid 0.1867488 
Run 24 stress 9.716907e-05 
... Procrustes: rmse 0.1509008  max resid 0.2618182 
Run 25 stress 0 
... Procrustes: rmse 0.05973701  max resid 0.09446323 
Run 26 stress 0 
... Procrustes: rmse 0.08943409  max resid 0.1756147 
Run 27 stress 0 
... Procrustes: rmse 0.0844327  max resid 0.14415 
Run 28 stress 0 
... Procrustes: rmse 0.1119332  max resid 0.2013292 
Run 29 stress 1.980986e-05 
... Procrustes: rmse 0.06570038  max resid 0.1169952 
Run 30 stress 0.2761354 
Run 31 stress 0 
... Procrustes: rmse 0.07770718  max resid 0.1074483 
Run 32 stress 0 
... Procrustes: rmse 0.06254715  max resid 0.09887051 
Run 33 stress 0 
... Procrustes: rmse 0.04758941  max resid 0.06036237 
Run 34 stress 0.1964001 
Run 35 stress 0.1964001 
Run 36 stress 0.1964001 
Run 37 stress 0.2761343 
Run 38 stress 0 
... Procrustes: rmse 0.05251142  max resid 0.0876186 
Run 39 stress 0.004699463 
Run 40 stress 0.1964001 
Run 41 stress 0 
... Procrustes: rmse 0.1306747  max resid 0.2260125 
Run 42 stress 0 
... Procrustes: rmse 0.09506064  max resid 0.1884457 
Run 43 stress 0 
... Procrustes: rmse 0.07195941  max resid 0.1353737 
Run 44 stress 9.83279e-05 
... Procrustes: rmse 0.1509008  max resid 0.261823 
Run 45 stress 0 
... Procrustes: rmse 0.06384242  max resid 0.1159743 
Run 46 stress 3.978645e-05 
... Procrustes: rmse 0.06397951  max resid 0.08485267 
Run 47 stress 9.82312e-05 
... Procrustes: rmse 0.150878  max resid 0.2617063 
Run 48 stress 8.665296e-05 
... Procrustes: rmse 0.08506109  max resid 0.1365683 
Run 49 stress 9.70663e-05 
... Procrustes: rmse 0.1508964  max resid 0.2618059 
Run 50 stress 9.490215e-05 
... Procrustes: rmse 0.1179302  max resid 0.2025423 
*** No convergence -- monoMDS stopping criteria:
     3: no. of iterations >= maxit
    38: stress < smin
     8: stress ratio > sratmax
     1: scale factor of the gradient < sfgrmin
stress is (nearly) zero: you may have insufficient data
[[1]]
[[1]]$x
 [1] 0.08235372 0.16922326 0.13399688 0.18851684 0.11184361 0.16554871 0.11063268 0.18048591
 [9] 0.10709883 0.16577753 0.16120027 0.14635979 0.20065758 0.14547214 0.16433578

[[1]]$y
 [1] 0.03627004 0.20772785 0.08460255 0.22588311 0.06460388 0.17297458 0.06400572 0.20985487
 [9] 0.04354659 0.18040217 0.16482254 0.15153341 0.25976659 0.10136720 0.16645123

[[1]]$yf
 [1] 0.03627004 0.20772785 0.08460255 0.22588311 0.06460388 0.17297458 0.06400572 0.20985487
 [9] 0.04354659 0.18040217 0.16482254 0.15153341 0.25976659 0.10136720 0.16645123


[[2]]

# analyze the four loci for mock feed sample F0_100
lapply(locs, bray_nmds_mock_feed, sodm_filtered_df = mock_feed_sodm_asvs_removed_dataframe, site = "F0_100")
'csv_outputs/bray_dissimilar/mockfeeds' already exists'nperm' >= set of all permutations: complete enumeration.
Set of permutations < 'minperm'. Generating entire set.
Run 0 stress 6.797137e-05 
Run 1 stress 0.1557467 
Run 2 stress 0.1557467 
Run 3 stress 7.562435e-05 
... Procrustes: rmse 0.08030631  max resid 0.1188797 
Run 4 stress 8.966116e-05 
... Procrustes: rmse 0.1487333  max resid 0.212373 
Run 5 stress 0.1557467 
Run 6 stress 0 
... New best solution
... Procrustes: rmse 0.1918413  max resid 0.2486181 
Run 7 stress 0.2761342 
Run 8 stress 0 
... Procrustes: rmse 0.1630701  max resid 0.2724451 
Run 9 stress 7.614869e-05 
... Procrustes: rmse 0.1670793  max resid 0.2436565 
Run 10 stress 0 
... Procrustes: rmse 0.09712496  max resid 0.1316051 
Run 11 stress 0 
... Procrustes: rmse 0.0999803  max resid 0.1220419 
Run 12 stress 0.1967694 
Run 13 stress 0 
... Procrustes: rmse 0.1549404  max resid 0.2672777 
Run 14 stress 2.45985e-05 
... Procrustes: rmse 0.2330788  max resid 0.3910971 
Run 15 stress 0 
... Procrustes: rmse 0.1467988  max resid 0.2363045 
Run 16 stress 0 
... Procrustes: rmse 0.1776624  max resid 0.285541 
Run 17 stress 0 
... Procrustes: rmse 0.1316287  max resid 0.2212684 
Run 18 stress 0.2269841 
Run 19 stress 0 
... Procrustes: rmse 0.08066602  max resid 0.122513 
Run 20 stress 0 
... Procrustes: rmse 0.04044139  max resid 0.055289 
Run 21 stress 0.1557467 
Run 22 stress 0 
... Procrustes: rmse 0.1626213  max resid 0.261945 
Run 23 stress 0 
... Procrustes: rmse 0.08670665  max resid 0.1182422 
Run 24 stress 0 
... Procrustes: rmse 0.1210269  max resid 0.213731 
Run 25 stress 0 
... Procrustes: rmse 0.1632461  max resid 0.272867 
Run 26 stress 5.778743e-05 
... Procrustes: rmse 0.219172  max resid 0.3830126 
Run 27 stress 0 
... Procrustes: rmse 0.2324768  max resid 0.3781966 
Run 28 stress 0 
... Procrustes: rmse 0.1949482  max resid 0.2730188 
Run 29 stress 0 
... Procrustes: rmse 0.1068732  max resid 0.166953 
Run 30 stress 0 
... Procrustes: rmse 0.2466887  max resid 0.3894845 
Run 31 stress 4.054386e-05 
... Procrustes: rmse 0.1660896  max resid 0.258395 
Run 32 stress 8.558735e-05 
... Procrustes: rmse 0.2336236  max resid 0.4060155 
Run 33 stress 0 
... Procrustes: rmse 0.1177261  max resid 0.181473 
Run 34 stress 0 
... Procrustes: rmse 0.1320465  max resid 0.1964872 
Run 35 stress 0 
... Procrustes: rmse 0.1238575  max resid 0.1643499 
Run 36 stress 0.1967694 
Run 37 stress 6.850994e-05 
... Procrustes: rmse 0.2105404  max resid 0.3336422 
Run 38 stress 0 
... Procrustes: rmse 0.1778579  max resid 0.2988372 
Run 39 stress 0 
... Procrustes: rmse 0.2457966  max resid 0.381166 
Run 40 stress 0 
... Procrustes: rmse 0.1979047  max resid 0.3160818 
Run 41 stress 3.263647e-05 
... Procrustes: rmse 0.08710919  max resid 0.128847 
Run 42 stress 0 
... Procrustes: rmse 0.157559  max resid 0.2497317 
Run 43 stress 0 
... Procrustes: rmse 0.145525  max resid 0.247641 
Run 44 stress 0 
... Procrustes: rmse 0.1654702  max resid 0.2621403 
Run 45 stress 1.314595e-05 
... Procrustes: rmse 0.08978755  max resid 0.1289944 
Run 46 stress 0.2761355 
Run 47 stress 0 
... Procrustes: rmse 0.1952367  max resid 0.2994856 
Run 48 stress 0 
... Procrustes: rmse 0.0486865  max resid 0.06676525 
Run 49 stress 0 
... Procrustes: rmse 0.1063841  max resid 0.196372 
Run 50 stress 7.812381e-05 
... Procrustes: rmse 0.1775323  max resid 0.2944729 
*** No convergence -- monoMDS stopping criteria:
    41: stress < smin
     6: stress ratio > sratmax
     3: scale factor of the gradient < sfgrmin
stress is (nearly) zero: you may have insufficient data
Run 0 stress 0 
Run 1 stress 0.1557467 
Run 2 stress 0 
... Procrustes: rmse 0.216707  max resid 0.3284185 
Run 3 stress 0 
... Procrustes: rmse 0.1239389  max resid 0.2093844 
Run 4 stress 8.438805e-05 
... Procrustes: rmse 0.2226681  max resid 0.3391351 
Run 5 stress 0.2130989 
Run 6 stress 7.976189e-05 
... Procrustes: rmse 0.2228066  max resid 0.3525509 
Run 7 stress 0 
... Procrustes: rmse 0.2430633  max resid 0.3746751 
Run 8 stress 0.2269842 
Run 9 stress 0 
... Procrustes: rmse 0.1875387  max resid 0.2526191 
Run 10 stress 0 
... Procrustes: rmse 0.1827241  max resid 0.2771838 
Run 11 stress 2.442165e-05 
... Procrustes: rmse 0.2293933  max resid 0.3454122 
Run 12 stress 6.515037e-05 
... Procrustes: rmse 0.2440448  max resid 0.3444438 
Run 13 stress 0 
... Procrustes: rmse 0.1821596  max resid 0.2501774 
Run 14 stress 0 
... Procrustes: rmse 0.2159835  max resid 0.2765069 
Run 15 stress 0.2761338 
Run 16 stress 0 
... Procrustes: rmse 0.1840612  max resid 0.2801757 
Run 17 stress 0 
... Procrustes: rmse 0.1889659  max resid 0.2538683 
Run 18 stress 0 
... Procrustes: rmse 0.196481  max resid 0.2786979 
Run 19 stress 0 
... Procrustes: rmse 0.2018784  max resid 0.2885867 
Run 20 stress 0 
... Procrustes: rmse 0.1808124  max resid 0.2383733 
Run 21 stress 0.1557467 
Run 22 stress 0.2269841 
Run 23 stress 9.955098e-05 
... Procrustes: rmse 0.1965028  max resid 0.2739226 
Run 24 stress 0 
... Procrustes: rmse 0.2067467  max resid 0.37563 
Run 25 stress 0.2130994 
Run 26 stress 0.1557467 
Run 27 stress 0 
... Procrustes: rmse 0.1873015  max resid 0.3136669 
Run 28 stress 9.662342e-05 
... Procrustes: rmse 0.1844764  max resid 0.2552976 
Run 29 stress 1.520534e-05 
... Procrustes: rmse 0.2022146  max resid 0.2753304 
Run 30 stress 0.2181459 
Run 31 stress 9.723643e-05 
... Procrustes: rmse 0.1075217  max resid 0.1644708 
Run 32 stress 0.1967694 
Run 33 stress 0 
... Procrustes: rmse 0.2105681  max resid 0.2807321 
Run 34 stress 0 
... Procrustes: rmse 0.2094619  max resid 0.3026186 
Run 35 stress 8.59255e-05 
... Procrustes: rmse 0.06414821  max resid 0.07604778 
Run 36 stress 0.2181459 
Run 37 stress 0 
... Procrustes: rmse 0.2116545  max resid 0.311221 
Run 38 stress 0.2672679 
Run 39 stress 0 
... Procrustes: rmse 0.1587251  max resid 0.2388922 
Run 40 stress 0.0002749278 
... Procrustes: rmse 0.1736291  max resid 0.2525672 
Run 41 stress 0 
... Procrustes: rmse 0.2172166  max resid 0.3481989 
Run 42 stress 0 
... Procrustes: rmse 0.2329948  max resid 0.3424033 
Run 43 stress 9.368023e-05 
... Procrustes: rmse 0.1995462  max resid 0.3626213 
Run 44 stress 0 
... Procrustes: rmse 0.1559475  max resid 0.216891 
Run 45 stress 7.549164e-05 
... Procrustes: rmse 0.2081239  max resid 0.3095146 
Run 46 stress 0 
... Procrustes: rmse 0.232797  max resid 0.3320413 
Run 47 stress 0 
... Procrustes: rmse 0.2050156  max resid 0.3668122 
Run 48 stress 0 
... Procrustes: rmse 0.2286724  max resid 0.3317656 
Run 49 stress 7.935514e-05 
... Procrustes: rmse 0.2375795  max resid 0.3395622 
Run 50 stress 0.2269841 
*** No convergence -- monoMDS stopping criteria:
     1: no. of iterations >= maxit
    36: stress < smin
     7: stress ratio > sratmax
     6: scale factor of the gradient < sfgrmin

'csv_outputs/bray_dissimilar/mockfeeds' already exists'nperm' >= set of all permutations: complete enumeration.
Set of permutations < 'minperm'. Generating entire set.
Run 0 stress 0 
Run 1 stress 0 
... Procrustes: rmse 0.200917  max resid 0.2729433 
Run 2 stress 0 
... Procrustes: rmse 0.1792084  max resid 0.2435658 
Run 3 stress 0 
... Procrustes: rmse 0.1042875  max resid 0.1523804 
Run 4 stress 0 
... Procrustes: rmse 0.1695369  max resid 0.227262 
Run 5 stress 0 
... Procrustes: rmse 0.2000718  max resid 0.3332387 
Run 6 stress 0.1970932 
Run 7 stress 1.975794e-05 
... Procrustes: rmse 0.139057  max resid 0.1892978 
Run 8 stress 8.485461e-05 
... Procrustes: rmse 0.160896  max resid 0.2064387 
Run 9 stress 0.1967694 
Run 10 stress 0.1967694 
Run 11 stress 6.842862e-05 
... Procrustes: rmse 0.227878  max resid 0.4086503 
Run 12 stress 0 
... Procrustes: rmse 0.1548529  max resid 0.2325908 
Run 13 stress 9.267035e-05 
... Procrustes: rmse 0.1227584  max resid 0.1668256 
Run 14 stress 0 
... Procrustes: rmse 0.1676108  max resid 0.2708664 
Run 15 stress 0.2761338 
Run 16 stress 9.729758e-05 
... Procrustes: rmse 0.1137458  max resid 0.1614339 
Run 17 stress 9.830937e-05 
... Procrustes: rmse 0.136207  max resid 0.1934379 
Run 18 stress 0 
... Procrustes: rmse 0.170082  max resid 0.2581504 
Run 19 stress 0 
... Procrustes: rmse 0.1395374  max resid 0.1921986 
Run 20 stress 0 
... Procrustes: rmse 0.1771517  max resid 0.281075 
Run 21 stress 0.1967694 
Run 22 stress 9.593632e-05 
... Procrustes: rmse 0.1757822  max resid 0.254933 
Run 23 stress 0 
... Procrustes: rmse 0.1679382  max resid 0.2445066 
Run 24 stress 0 
... Procrustes: rmse 0.215328  max resid 0.3876556 
Run 25 stress 0.2672679 
Run 26 stress 6.493077e-05 
... Procrustes: rmse 0.2121383  max resid 0.3650302 
Run 27 stress 0 
... Procrustes: rmse 0.1669448  max resid 0.2566071 
Run 28 stress 0.2181459 
Run 29 stress 0.2761345 
Run 30 stress 0.2181459 
Run 31 stress 0 
... Procrustes: rmse 0.1527509  max resid 0.2041601 
Run 32 stress 0.2181459 
Run 33 stress 0.1967694 
Run 34 stress 0 
... Procrustes: rmse 0.1592293  max resid 0.2547942 
Run 35 stress 0 
... Procrustes: rmse 0.09241022  max resid 0.1138217 
Run 36 stress 8.603144e-05 
... Procrustes: rmse 0.2188329  max resid 0.2805109 
Run 37 stress 9.855702e-05 
... Procrustes: rmse 0.2394081  max resid 0.4308188 
Run 38 stress 0.2672326 
Run 39 stress 0 
... Procrustes: rmse 0.1646802  max resid 0.2675111 
Run 40 stress 4.756819e-05 
... Procrustes: rmse 0.2499768  max resid 0.3354394 
Run 41 stress 0 
... Procrustes: rmse 0.1700967  max resid 0.3107606 
Run 42 stress 0.1967694 
Run 43 stress 0 
... Procrustes: rmse 0.1994484  max resid 0.3325655 
Run 44 stress 0 
... Procrustes: rmse 0.1817738  max resid 0.2790491 
Run 45 stress 8.214697e-05 
... Procrustes: rmse 0.1802124  max resid 0.3089334 
Run 46 stress 0.1967694 
Run 47 stress 0 
... Procrustes: rmse 0.2311707  max resid 0.4127761 
Run 48 stress 0.2269841 
Run 49 stress 0 
... Procrustes: rmse 0.1642674  max resid 0.2280852 
Run 50 stress 7.171528e-05 
... Procrustes: rmse 0.1727568  max resid 0.260029 
*** No convergence -- monoMDS stopping criteria:
    35: stress < smin
     9: stress ratio > sratmax
     6: scale factor of the gradient < sfgrmin
stress is (nearly) zero: you may have insufficient data

'csv_outputs/bray_dissimilar/mockfeeds' already exists'nperm' >= set of all permutations: complete enumeration.
Set of permutations < 'minperm'. Generating entire set.
Run 0 stress 1.883529e-05 
Run 1 stress 0 
... New best solution
... Procrustes: rmse 0.1189936  max resid 0.182086 
Run 2 stress 0 
... Procrustes: rmse 0.1251948  max resid 0.2458473 
Run 3 stress 0 
... Procrustes: rmse 0.1382548  max resid 0.2108325 
Run 4 stress 0 
... Procrustes: rmse 0.0677733  max resid 0.09909404 
Run 5 stress 0.1967694 
Run 6 stress 0 
... Procrustes: rmse 0.1268782  max resid 0.2126362 
Run 7 stress 9.768749e-05 
... Procrustes: rmse 0.1401893  max resid 0.253471 
Run 8 stress 0 
... Procrustes: rmse 0.151565  max resid 0.1965376 
Run 9 stress 0 
... Procrustes: rmse 0.1570525  max resid 0.2336614 
Run 10 stress 0 
... Procrustes: rmse 0.1597817  max resid 0.2649448 
Run 11 stress 0.2181459 
Run 12 stress 0 
... Procrustes: rmse 0.169898  max resid 0.2155338 
Run 13 stress 0 
... Procrustes: rmse 0.1659109  max resid 0.3556193 
Run 14 stress 0 
... Procrustes: rmse 0.1969086  max resid 0.2867465 
Run 15 stress 8.772143e-05 
... Procrustes: rmse 0.09760409  max resid 0.1242714 
Run 16 stress 2.358302e-05 
... Procrustes: rmse 0.1829463  max resid 0.268296 
Run 17 stress 9.512092e-05 
... Procrustes: rmse 0.127823  max resid 0.1718707 
Run 18 stress 0 
... Procrustes: rmse 0.1792446  max resid 0.3719052 
Run 19 stress 0 
... Procrustes: rmse 0.06980143  max resid 0.1054105 
Run 20 stress 0 
... Procrustes: rmse 0.1279696  max resid 0.2320436 
Run 21 stress 0 
... Procrustes: rmse 0.04817071  max resid 0.07572467 
Run 22 stress 0.2672328 
Run 23 stress 0 
... Procrustes: rmse 0.1481909  max resid 0.236068 
Run 24 stress 0 
... Procrustes: rmse 0.1613522  max resid 0.1946558 
Run 25 stress 9.94811e-05 
... Procrustes: rmse 0.1824641  max resid 0.2358877 
Run 26 stress 0 
... Procrustes: rmse 0.1727518  max resid 0.3489211 
Run 27 stress 0 
... Procrustes: rmse 0.1742554  max resid 0.2247009 
Run 28 stress 0 
... Procrustes: rmse 0.05942961  max resid 0.08747323 
Run 29 stress 0 
... Procrustes: rmse 0.1120925  max resid 0.1841444 
Run 30 stress 3.903664e-05 
... Procrustes: rmse 0.1325154  max resid 0.1912761 
Run 31 stress 5.399369e-05 
... Procrustes: rmse 0.1010359  max resid 0.1467465 
Run 32 stress 7.379184e-05 
... Procrustes: rmse 0.1331372  max resid 0.1950281 
Run 33 stress 0 
... Procrustes: rmse 0.1596573  max resid 0.2780751 
Run 34 stress 0 
... Procrustes: rmse 0.1545245  max resid 0.3209774 
Run 35 stress 6.920823e-05 
... Procrustes: rmse 0.112497  max resid 0.2057306 
Run 36 stress 0 
... Procrustes: rmse 0.1150425  max resid 0.1881103 
Run 37 stress 0.1967694 
Run 38 stress 0 
... Procrustes: rmse 0.05315167  max resid 0.1032802 
Run 39 stress 1.655269e-05 
... Procrustes: rmse 0.1448603  max resid 0.2697769 
Run 40 stress 0 
... Procrustes: rmse 0.1612889  max resid 0.1910241 
Run 41 stress 2.114832e-09 
... Procrustes: rmse 0.1841392  max resid 0.2444196 
Run 42 stress 0 
... Procrustes: rmse 0.1425155  max resid 0.2249561 
Run 43 stress 0.1967694 
Run 44 stress 0 
... Procrustes: rmse 0.1768091  max resid 0.2551034 
Run 45 stress 0 
... Procrustes: rmse 0.1698371  max resid 0.3456138 
Run 46 stress 0 
... Procrustes: rmse 0.1529447  max resid 0.2827875 
Run 47 stress 0.2181459 
Run 48 stress 0 
... Procrustes: rmse 0.05269924  max resid 0.08362616 
Run 49 stress 0 
... Procrustes: rmse 0.1547511  max resid 0.2465553 
Run 50 stress 0.2672326 
*** No convergence -- monoMDS stopping criteria:
    43: stress < smin
     6: stress ratio > sratmax
     1: scale factor of the gradient < sfgrmin
stress is (nearly) zero: you may have insufficient data

[[1]]
[[1]][[1]]
[[1]][[1]]$x
 [1] 0.455630579 0.031687447 0.011165044 0.467932180 0.456814980 0.481128614 0.448182873
 [8] 0.019509172 0.009092947 0.039385854 0.493691249 0.482584407 0.460410026 0.449150152
[15] 0.023656561

[[1]][[1]]$y
 [1] 6.517246e-01 4.849436e-01 8.138855e-02 6.736325e-01 6.517246e-01 1.128445e+00
 [7] 5.893142e-01 4.222970e-01 4.941636e-13 5.393635e-01 1.135606e+00 1.128445e+00
[13] 6.568494e-01 5.893142e-01 4.222970e-01

[[1]][[1]]$yf
 [1] 6.517246e-01 4.849436e-01 8.138855e-02 6.736325e-01 6.517246e-01 1.128445e+00
 [7] 5.893142e-01 4.222970e-01 4.941636e-13 5.393635e-01 1.135606e+00 1.128445e+00
[13] 6.568494e-01 5.893142e-01 4.222970e-01


[[1]][[2]]


[[2]]
[[2]][[1]]
[[2]][[1]]$x
 [1] 0.020370742 0.021775514 0.536277585 0.527567678 0.542073274 0.005729939 0.529162348
 [8] 0.520405651 0.535017731 0.527317058 0.518564217 0.533141106 0.010204119 0.007195109
[15] 0.015121781

[[2]][[1]]$y
 [1] 0.04039450 0.04312173 1.07137806 1.05398223 1.08296778 0.00398703 1.05716121 1.03967373
 [9] 1.06883600 1.05345375 1.03596315 1.06513158 0.01763126 0.01188034 0.02949857

[[2]][[1]]$yf
 [1] 0.04039450 0.04312173 1.07137806 1.05398223 1.08296778 0.00398703 1.05716121 1.03967373
 [9] 1.06883600 1.05345375 1.03596315 1.06513158 0.01763126 0.01188034 0.02949857


[[2]][[2]]


[[3]]
[[3]][[1]]
[[3]][[1]]$x
 [1] 0.019042371 0.023817717 0.503298143 0.495909258 0.498116609 0.009214567 0.485746569
 [8] 0.478316420 0.480640216 0.484014906 0.476718469 0.478965566 0.008037243 0.006246801
[15] 0.005830554

[[3]][[1]]$y
 [1] 0.036924981 0.047630271 1.005825904 0.990987984 0.995474004 0.016688333 0.970703879
 [8] 0.955938452 0.960452131 0.967299934 0.952643143 0.957195285 0.016039401 0.013371015
[15] 0.005060069

[[3]][[1]]$yf
 [1] 0.036924981 0.047630271 1.005825904 0.990987984 0.995474004 0.016688333 0.970703879
 [8] 0.955938452 0.960452131 0.967299934 0.952643143 0.957195285 0.016039401 0.013371015
[15] 0.005060069


[[3]][[2]]


[[4]]
[[4]][[1]]
[[4]][[1]]$x
 [1] 0.05744362 0.62639996 0.61813302 0.16695428 0.61361505 0.60941196 0.60119243 0.12118886
 [9] 0.59666234 0.01744839 0.52985464 0.01718967 0.52315263 0.01498784 0.51574041

[[4]][[1]]$y
 [1] 0.34509345 1.53479093 1.36136022 0.84278066 1.34760283 1.22941516 1.09635209 0.50452276
 [9] 1.08129922 0.31275289 0.95182549 0.31233944 0.95146566 0.01613203 0.93543738

[[4]][[1]]$yf
 [1] 0.34509345 1.53479093 1.36136022 0.84278066 1.34760283 1.22941516 1.09635209 0.50452276
 [9] 1.08129922 0.31275289 0.95182549 0.31233944 0.95146566 0.01613203 0.93543738


[[4]][[2]]

Filler 1

# lapply the function with all four loci
lapply(locs, bray_nmds_mock_feed, sodm_filtered_df = mock_feed_sodm_asvs_removed_dataframe, site = "F1_0")
'csv_outputs/bray_dissimilar/mockfeeds' already exists'nperm' >= set of all permutations: complete enumeration.
Set of permutations < 'minperm'. Generating entire set.
Run 0 stress 0 
Run 1 stress 0 
... Procrustes: rmse 0.08306481  max resid 0.1500837 
Run 2 stress 8.393474e-05 
... Procrustes: rmse 0.0650365  max resid 0.1016619 
Run 3 stress 9.601771e-05 
... Procrustes: rmse 0.1508988  max resid 0.2618136 
Run 4 stress 0 
... Procrustes: rmse 0.09565963  max resid 0.1719531 
Run 5 stress 9.762288e-05 
... Procrustes: rmse 0.1508948  max resid 0.2618009 
Run 6 stress 0 
... Procrustes: rmse 0.05516981  max resid 0.08298733 
Run 7 stress 0.005052253 
Run 8 stress 9.545577e-05 
... Procrustes: rmse 0.1508969  max resid 0.2618038 
Run 9 stress 6.304464e-05 
... Procrustes: rmse 0.06759018  max resid 0.1260851 
Run 10 stress 0 
... Procrustes: rmse 0.06590909  max resid 0.1190405 
Run 11 stress 3.912468e-05 
... Procrustes: rmse 0.07810179  max resid 0.1189405 
Run 12 stress 0.1964001 
Run 13 stress 0 
... Procrustes: rmse 0.05915666  max resid 0.1147621 
Run 14 stress 1.210162e-05 
... Procrustes: rmse 0.1275159  max resid 0.2214862 
Run 15 stress 0.1964001 
Run 16 stress 7.15227e-05 
... Procrustes: rmse 0.06823941  max resid 0.09896617 
Run 17 stress 7.930743e-05 
... Procrustes: rmse 0.1418135  max resid 0.2454811 
Run 18 stress 0.2181459 
Run 19 stress 0.004773638 
Run 20 stress 0 
... Procrustes: rmse 0.05536676  max resid 0.1114028 
Run 21 stress 0 
... Procrustes: rmse 0.05288896  max resid 0.07930563 
Run 22 stress 0 
... Procrustes: rmse 0.07216272  max resid 0.1259475 
Run 23 stress 0 
... Procrustes: rmse 0.09203779  max resid 0.1867488 
Run 24 stress 9.716907e-05 
... Procrustes: rmse 0.1509008  max resid 0.2618182 
Run 25 stress 0 
... Procrustes: rmse 0.05973701  max resid 0.09446323 
Run 26 stress 0 
... Procrustes: rmse 0.08943409  max resid 0.1756147 
Run 27 stress 0 
... Procrustes: rmse 0.0844327  max resid 0.14415 
Run 28 stress 0 
... Procrustes: rmse 0.1119332  max resid 0.2013292 
Run 29 stress 1.980986e-05 
... Procrustes: rmse 0.06570038  max resid 0.1169952 
Run 30 stress 0.2761354 
Run 31 stress 0 
... Procrustes: rmse 0.07770718  max resid 0.1074483 
Run 32 stress 0 
... Procrustes: rmse 0.06254715  max resid 0.09887051 
Run 33 stress 0 
... Procrustes: rmse 0.04758941  max resid 0.06036237 
Run 34 stress 0.1964001 
Run 35 stress 0.1964001 
Run 36 stress 0.1964001 
Run 37 stress 0.2761343 
Run 38 stress 0 
... Procrustes: rmse 0.05251142  max resid 0.0876186 
Run 39 stress 0.004699463 
Run 40 stress 0.1964001 
Run 41 stress 0 
... Procrustes: rmse 0.1306747  max resid 0.2260125 
Run 42 stress 0 
... Procrustes: rmse 0.09506064  max resid 0.1884457 
Run 43 stress 0 
... Procrustes: rmse 0.07195941  max resid 0.1353737 
Run 44 stress 9.83279e-05 
... Procrustes: rmse 0.1509008  max resid 0.261823 
Run 45 stress 0 
... Procrustes: rmse 0.06384242  max resid 0.1159743 
Run 46 stress 3.978645e-05 
... Procrustes: rmse 0.06397951  max resid 0.08485267 
Run 47 stress 9.82312e-05 
... Procrustes: rmse 0.150878  max resid 0.2617063 
Run 48 stress 8.665296e-05 
... Procrustes: rmse 0.08506109  max resid 0.1365683 
Run 49 stress 9.70663e-05 
... Procrustes: rmse 0.1508964  max resid 0.2618059 
Run 50 stress 9.490215e-05 
... Procrustes: rmse 0.1179302  max resid 0.2025423 
*** No convergence -- monoMDS stopping criteria:
     3: no. of iterations >= maxit
    38: stress < smin
     8: stress ratio > sratmax
     1: scale factor of the gradient < sfgrmin
stress is (nearly) zero: you may have insufficient data
Run 0 stress 0 
Run 1 stress 9.84425e-05 
... Procrustes: rmse 0.05796188  max resid 0.09363277 
Run 2 stress 9.192271e-05 
... Procrustes: rmse 0.05793028  max resid 0.09358927 
Run 3 stress 0.04733294 
Run 4 stress 9.141673e-05 
... Procrustes: rmse 0.08849435  max resid 0.1345743 
Run 5 stress 0.1967694 
Run 6 stress 9.290967e-05 
... Procrustes: rmse 0.05792952  max resid 0.09358641 
Run 7 stress 0.04733513 
Run 8 stress 0.07049135 
Run 9 stress 9.76217e-05 
... Procrustes: rmse 0.03149038  max resid 0.04717506 
Run 10 stress 0 
... Procrustes: rmse 0.07465643  max resid 0.1020887 
Run 11 stress 0.2006011 
Run 12 stress 0 
... Procrustes: rmse 0.05781496  max resid 0.07364721 
Run 13 stress 0 
... Procrustes: rmse 0.08604689  max resid 0.1313007 
Run 14 stress 0.04733473 
Run 15 stress 0 
... Procrustes: rmse 0.02333959  max resid 0.0360221 
Run 16 stress 0.04733407 
Run 17 stress 0.04733319 
Run 18 stress 0.2006012 
Run 19 stress 0.04733288 
Run 20 stress 0.2181459 
Run 21 stress 0 
... Procrustes: rmse 0.008697031  max resid 0.01219564 
Run 22 stress 0.07049114 
Run 23 stress 0.04733426 
Run 24 stress 0.2181459 
Run 25 stress 0 
... Procrustes: rmse 0.1113266  max resid 0.175125 
Run 26 stress 0.2006012 
Run 27 stress 9.16307e-05 
... Procrustes: rmse 0.03452735  max resid 0.05457119 
Run 28 stress 0 
... Procrustes: rmse 0.08900288  max resid 0.1360343 
Run 29 stress 0.1967694 
Run 30 stress 9.805726e-05 
... Procrustes: rmse 0.0245335  max resid 0.04198703 
Run 31 stress 0 
... Procrustes: rmse 0.07694084  max resid 0.1091291 
Run 32 stress 0.07048915 
Run 33 stress 0.04733381 
Run 34 stress 0.04733334 
Run 35 stress 0.1620083 
Run 36 stress 0.2269842 
Run 37 stress 0.2006011 
Run 38 stress 0.1967694 
Run 39 stress 0 
... Procrustes: rmse 0.05828024  max resid 0.08635312 
Run 40 stress 0.07049115 
Run 41 stress 0.2269841 
Run 42 stress 9.327995e-05 
... Procrustes: rmse 0.04306195  max resid 0.07538903 
Run 43 stress 0 
... Procrustes: rmse 0.05405981  max resid 0.08557559 
Run 44 stress 0.04733354 
Run 45 stress 9.840137e-05 
... Procrustes: rmse 0.05797403  max resid 0.09365241 
Run 46 stress 0.047335 
Run 47 stress 0 
... Procrustes: rmse 0.03770873  max resid 0.05329281 
Run 48 stress 9.996972e-05 
... Procrustes: rmse 0.0579823  max resid 0.09366323 
Run 49 stress 9.794911e-05 
... Procrustes: rmse 0.02794148  max resid 0.044609 
Run 50 stress 9.76326e-05 
... Procrustes: rmse 0.05796927  max resid 0.0936448 
*** No convergence -- monoMDS stopping criteria:
    23: stress < smin
    22: stress ratio > sratmax
     5: scale factor of the gradient < sfgrmin

'csv_outputs/bray_dissimilar/mockfeeds' already exists'nperm' >= set of all permutations: complete enumeration.
Set of permutations < 'minperm'. Generating entire set.
Run 0 stress 9.288062e-05 
Run 1 stress 9.935409e-05 
... Procrustes: rmse 0.01927745  max resid 0.03054252 
Run 2 stress 0.2672326 
Run 3 stress 9.494183e-05 
... Procrustes: rmse 0.02136947  max resid 0.03540566 
Run 4 stress 0.0001672882 
... Procrustes: rmse 0.2998376  max resid 0.435781 
Run 5 stress 0.0002487257 
... Procrustes: rmse 0.2995368  max resid 0.4357041 
Run 6 stress 0.1970932 
Run 7 stress 9.862627e-05 
... Procrustes: rmse 0.0709689  max resid 0.08719569 
Run 8 stress 8.325195e-05 
... New best solution
... Procrustes: rmse 0.1037393  max resid 0.1665368 
Run 9 stress 0.1967694 
Run 10 stress 0.1967694 
Run 11 stress 9.980822e-05 
... Procrustes: rmse 0.2982585  max resid 0.4416807 
Run 12 stress 9.671238e-05 
... Procrustes: rmse 0.03270725  max resid 0.05584652 
Run 13 stress 8.259271e-05 
... New best solution
... Procrustes: rmse 0.04375163  max resid 0.06171771 
Run 14 stress 9.865693e-05 
... Procrustes: rmse 0.3097449  max resid 0.4613929 
Run 15 stress 0.2761338 
Run 16 stress 9.417506e-05 
... Procrustes: rmse 0.09823271  max resid 0.1392558 
Run 17 stress 0.0002334998 
... Procrustes: rmse 0.3092202  max resid 0.461155 
Run 18 stress 0.0002002533 
... Procrustes: rmse 0.3093261  max resid 0.461202 
Run 19 stress 9.77665e-05 
... Procrustes: rmse 0.09650949  max resid 0.1341966 
Run 20 stress 0.0001700821 
... Procrustes: rmse 0.3094269  max resid 0.4612464 
Run 21 stress 8.1437e-05 
... New best solution
... Procrustes: rmse 0.3097858  max resid 0.4613998 
Run 22 stress 0 
... New best solution
... Procrustes: rmse 0.3070755  max resid 0.5145376 
Run 23 stress 8.904473e-05 
... Procrustes: rmse 0.1163195  max resid 0.1895859 
Run 24 stress 0.0001143681 
... Procrustes: rmse 0.306872  max resid 0.4426481 
Run 25 stress 9.571803e-05 
... Procrustes: rmse 0.06819767  max resid 0.1180618 
Run 26 stress 0.0002413045 
... Procrustes: rmse 0.3064116  max resid 0.4425511 
Run 27 stress 9.465741e-05 
... Procrustes: rmse 0.3070461  max resid 0.4428306 
Run 28 stress 0.1967694 
Run 29 stress 0.2761345 
Run 30 stress 0.2162637 
Run 31 stress 7.392473e-05 
... Procrustes: rmse 0.1293841  max resid 0.2123618 
Run 32 stress 0.0002153372 
... Procrustes: rmse 0.3065  max resid 0.4425697 
Run 33 stress 0.1967694 
Run 34 stress 9.997403e-05 
... Procrustes: rmse 0.3068736  max resid 0.4426477 
Run 35 stress 9.653248e-05 
... Procrustes: rmse 0.130319  max resid 0.2185764 
Run 36 stress 9.932296e-05 
... Procrustes: rmse 0.1306913  max resid 0.2187037 
Run 37 stress 8.652972e-05 
... Procrustes: rmse 0.3070574  max resid 0.442818 
Run 38 stress 9.816365e-05 
... Procrustes: rmse 0.1303265  max resid 0.2185714 
Run 39 stress 0.0001534673 
... Procrustes: rmse 0.306696  max resid 0.4426111 
Run 40 stress 0.0002483038 
... Procrustes: rmse 0.3063834  max resid 0.4425453 
Run 41 stress 9.600741e-05 
... Procrustes: rmse 0.3070428  max resid 0.442832 
Run 42 stress 0.1967694 
Run 43 stress 0.0001062605 
... Procrustes: rmse 0.3068523  max resid 0.4426432 
Run 44 stress 6.707316e-05 
... Procrustes: rmse 0.06881967  max resid 0.119313 
Run 45 stress 9.543737e-05 
... Procrustes: rmse 0.3070428  max resid 0.4428315 
Run 46 stress 0.1967694 
Run 47 stress 9.08907e-05 
... Procrustes: rmse 0.3070547  max resid 0.4428253 
Run 48 stress 0.2269841 
Run 49 stress 8.98486e-05 
... Procrustes: rmse 0.03419239  max resid 0.06447473 
Run 50 stress 9.330837e-05 
... Procrustes: rmse 0.0531996  max resid 0.08947516 
*** No convergence -- monoMDS stopping criteria:
    11: no. of iterations >= maxit
    27: stress < smin
    10: stress ratio > sratmax
     2: scale factor of the gradient < sfgrmin
stress is (nearly) zero: you may have insufficient data

'csv_outputs/bray_dissimilar/mockfeeds' already exists'nperm' >= set of all permutations: complete enumeration.
Set of permutations < 'minperm'. Generating entire set.
Run 0 stress 0.0004669906 
Run 1 stress 0.276134 
Run 2 stress 9.492375e-05 
... New best solution
... Procrustes: rmse 0.1094817  max resid 0.1950747 
Run 3 stress 0.1420473 
Run 4 stress 0.001917046 
Run 5 stress 0.001346452 
Run 6 stress 9.832348e-05 
... Procrustes: rmse 0.1093233  max resid 0.2191431 
Run 7 stress 0.005107424 
Run 8 stress 0.001539236 
Run 9 stress 9.799846e-05 
... Procrustes: rmse 0.0174658  max resid 0.03175275 
Run 10 stress 9.858956e-05 
... Procrustes: rmse 0.05003124  max resid 0.09455763 
Run 11 stress 9.671445e-05 
... Procrustes: rmse 0.05685749  max resid 0.09948346 
Run 12 stress 0.202923 
Run 13 stress 0.0002418935 
... Procrustes: rmse 0.1127767  max resid 0.2187444 
Run 14 stress 0.001909211 
Run 15 stress 0.2159914 
Run 16 stress 0.0007357664 
Run 17 stress 0.002043995 
Run 18 stress 0.001562868 
Run 19 stress 0.001774865 
Run 20 stress 9.976101e-05 
... Procrustes: rmse 0.03926445  max resid 0.07461661 
Run 21 stress 0.002192585 
Run 22 stress 0.002294747 
Run 23 stress 9.899158e-05 
... Procrustes: rmse 0.1331164  max resid 0.2750697 
Run 24 stress 0.002191628 
Run 25 stress 9.123e-05 
... New best solution
... Procrustes: rmse 0.03559199  max resid 0.06037134 
Run 26 stress 9.942274e-05 
... Procrustes: rmse 0.2224874  max resid 0.4728508 
Run 27 stress 0.2181459 
Run 28 stress 9.723968e-05 
... Procrustes: rmse 0.02377437  max resid 0.0392155 
Run 29 stress 9.611648e-05 
... Procrustes: rmse 0.08741644  max resid 0.1686624 
Run 30 stress 0.001136239 
Run 31 stress 0.0003363814 
... Procrustes: rmse 0.2532811  max resid 0.4645238 
Run 32 stress 0.0007536452 
Run 33 stress 9.870571e-05 
... Procrustes: rmse 0.07105116  max resid 0.1356258 
Run 34 stress 0.001865427 
Run 35 stress 0.1420473 
Run 36 stress 0.001677937 
Run 37 stress 9.635011e-05 
... Procrustes: rmse 0.02560996  max resid 0.04562696 
Run 38 stress 9.880459e-05 
... Procrustes: rmse 0.0426541  max resid 0.07618848 
Run 39 stress 0.002961839 
Run 40 stress 0.202923 
Run 41 stress 0.0004419442 
... Procrustes: rmse 0.1508734  max resid 0.2778805 
Run 42 stress 0.0007780449 
Run 43 stress 0.001607698 
Run 44 stress 9.535506e-05 
... Procrustes: rmse 0.07076021  max resid 0.1304869 
Run 45 stress 0.003001466 
Run 46 stress 0.001432106 
Run 47 stress 9.871739e-05 
... Procrustes: rmse 0.1106065  max resid 0.2158964 
Run 48 stress 0.00114001 
Run 49 stress 0.2181459 
Run 50 stress 0.1420473 
*** No convergence -- monoMDS stopping criteria:
    25: no. of iterations >= maxit
    16: stress < smin
     5: stress ratio > sratmax
     4: scale factor of the gradient < sfgrmin
stress is (nearly) zero: you may have insufficient dataskipping half-change scaling: too few points below threshold

[[1]]
[[1]][[1]]
[[1]][[1]]$x
 [1] 0.08235372 0.16922326 0.13399688 0.18851684 0.11184361 0.16554871 0.11063268 0.18048591
 [9] 0.10709883 0.16577753 0.16120027 0.14635979 0.20065758 0.14547214 0.16433578

[[1]][[1]]$y
 [1] 0.03627004 0.20772785 0.08460255 0.22588311 0.06460388 0.17297458 0.06400572 0.20985487
 [9] 0.04354659 0.18040217 0.16482254 0.15153341 0.25976659 0.10136720 0.16645123

[[1]][[1]]$yf
 [1] 0.03627004 0.20772785 0.08460255 0.22588311 0.06460388 0.17297458 0.06400572 0.20985487
 [9] 0.04354659 0.18040217 0.16482254 0.15153341 0.25976659 0.10136720 0.16645123


[[1]][[2]]


[[2]]
[[2]][[1]]
[[2]][[1]]$x
 [1] 0.17188052 0.11550327 0.16185618 0.11945687 0.14165637 0.15403252 0.12319280 0.12714596
 [9] 0.19578535 0.17324048 0.09524785 0.11246285 0.15984646 0.23541141 0.15059186

[[2]][[1]]$y
 [1] 0.23019707 0.10139864 0.22679648 0.11216333 0.15433111 0.18730854 0.13309154 0.13309220
 [9] 0.28206999 0.24306098 0.05764288 0.09951253 0.18843030 0.34128563 0.15699641

[[2]][[1]]$yf
 [1] 0.23019707 0.10139864 0.22679648 0.11216333 0.15433111 0.18730854 0.13309154 0.13309220
 [9] 0.28206999 0.24306098 0.05764288 0.09951253 0.18843030 0.34128563 0.15699641


[[2]][[2]]


[[3]]
[[3]][[1]]
[[3]][[1]]$x
 [1] 0.08654040 0.09198057 0.14673668 0.12506019 0.12096826 0.08199491 0.11060969 0.09325268
 [9] 0.09229807 0.12407869 0.08475139 0.08816411 0.06447852 0.06233777 0.02992395

[[3]][[1]]$y
 [1] 0.10685122 0.11149657 0.25419486 0.19916463 0.19567153 0.10664459 0.15099400 0.12713997
 [9] 0.11877822 0.19580864 0.10670595 0.10846333 0.10649818 0.09756169 0.01163680

[[3]][[1]]$yf
 [1] 0.10685122 0.11149657 0.25419486 0.19916463 0.19567153 0.10664459 0.15099400 0.12713997
 [9] 0.11877822 0.19580864 0.10670595 0.10846333 0.10649818 0.09756169 0.01163680


[[3]][[2]]


[[4]]
[[4]][[1]]
[[4]][[1]]$x
 [1] 0.9352071 0.8379840 0.2250675 0.2428324 0.2359233 0.3431216 0.9032836 0.9496608 0.9455931
[10] 0.8005636 0.8799819 0.8581374 0.1168503 0.1276983 0.1453950

[[4]][[1]]$y
 [1] 0.9486908259 0.8976707534 0.0008126971 0.0012892839 0.0006862254 0.8296463185
 [7] 0.9487862071 0.9496608466 0.9492865248 0.8970804407 0.8975695046 0.8977535755
[13] 0.0008756401 0.0006841696 0.0006316081

[[4]][[1]]$yf
 [1] 0.9487385165 0.8976646112 0.0007494612 0.0012892839 0.0007494612 0.8296463185
 [7] 0.9487385165 0.9496608466 0.9492865248 0.8970804407 0.8976646112 0.8976646112
[13] 0.0007304726 0.0007304726 0.0007304726


[[4]][[2]]

# analyze sample F1_10
lapply(locs, bray_nmds_mock_feed, sodm_filtered_df = mock_feed_sodm_asvs_removed_dataframe, site = "F1_10")
'csv_outputs/bray_dissimilar/mockfeeds' already exists'nperm' >= set of all permutations: complete enumeration.
Set of permutations < 'minperm'. Generating entire set.
Run 0 stress 0 
Run 1 stress 0.2761359 
Run 2 stress 0 
... Procrustes: rmse 0.1782514  max resid 0.3041158 
Run 3 stress 0.276135 
Run 4 stress 7.66081e-05 
... Procrustes: rmse 0.2344818  max resid 0.3668063 
Run 5 stress 5.015669e-05 
... Procrustes: rmse 0.05616418  max resid 0.1050068 
Run 6 stress 0 
... Procrustes: rmse 0.04417714  max resid 0.07079991 
Run 7 stress 0.0008303259 
Run 8 stress 0.1420473 
Run 9 stress 0.001924173 
Run 10 stress 9.684896e-05 
... Procrustes: rmse 0.2523453  max resid 0.3905902 
Run 11 stress 0 
... Procrustes: rmse 0.171424  max resid 0.2945327 
Run 12 stress 0.1420473 
Run 13 stress 7.792994e-05 
... Procrustes: rmse 0.219393  max resid 0.3191929 
Run 14 stress 0.1967694 
Run 15 stress 8.119786e-05 
... Procrustes: rmse 0.05195433  max resid 0.08525008 
Run 16 stress 0 
... Procrustes: rmse 0.1510171  max resid 0.2482222 
Run 17 stress 0 
... Procrustes: rmse 0.2236458  max resid 0.3640034 
Run 18 stress 0.1420473 
Run 19 stress 0.0004255954 
... Procrustes: rmse 0.238965  max resid 0.3759676 
Run 20 stress 0 
... Procrustes: rmse 0.1010101  max resid 0.178044 
Run 21 stress 8.971604e-05 
... Procrustes: rmse 0.2374718  max resid 0.3491048 
Run 22 stress 0 
... Procrustes: rmse 0.1874702  max resid 0.318879 
Run 23 stress 9.277236e-06 
... Procrustes: rmse 0.2201936  max resid 0.2971146 
Run 24 stress 6.871951e-05 
... Procrustes: rmse 0.07134347  max resid 0.1072856 
Run 25 stress 0 
... Procrustes: rmse 0.2160544  max resid 0.3267475 
Run 26 stress 9.537637e-05 
... Procrustes: rmse 0.2602977  max resid 0.3376999 
Run 27 stress 0 
... Procrustes: rmse 0.1732755  max resid 0.2359424 
Run 28 stress 0 
... Procrustes: rmse 0.2110359  max resid 0.3146671 
Run 29 stress 9.737606e-05 
... Procrustes: rmse 0.06191323  max resid 0.1033323 
Run 30 stress 0 
... Procrustes: rmse 0.2311834  max resid 0.3309575 
Run 31 stress 0 
... Procrustes: rmse 0.2523026  max resid 0.3825019 
Run 32 stress 6.439155e-05 
... Procrustes: rmse 0.2673991  max resid 0.3576358 
Run 33 stress 0 
... Procrustes: rmse 0.1757631  max resid 0.3031776 
Run 34 stress 9.249799e-05 
... Procrustes: rmse 0.2105243  max resid 0.3388449 
Run 35 stress 8.411932e-05 
... Procrustes: rmse 0.06075886  max resid 0.1010699 
Run 36 stress 0 
... Procrustes: rmse 0.06367534  max resid 0.1162029 
Run 37 stress 9.307845e-05 
... Procrustes: rmse 0.1873243  max resid 0.3223229 
Run 38 stress 2.944851e-06 
... Procrustes: rmse 0.04917603  max resid 0.07568098 
Run 39 stress 0.0001724431 
... Procrustes: rmse 0.2495602  max resid 0.3833985 
Run 40 stress 0.1420473 
Run 41 stress 0 
... Procrustes: rmse 0.1569581  max resid 0.2203168 
Run 42 stress 9.971866e-05 
... Procrustes: rmse 0.2580352  max resid 0.3930695 
Run 43 stress 0 
... Procrustes: rmse 0.1520931  max resid 0.2414392 
Run 44 stress 0.1420473 
Run 45 stress 0 
... Procrustes: rmse 0.175364  max resid 0.3003158 
Run 46 stress 0 
... Procrustes: rmse 0.1453873  max resid 0.2099739 
Run 47 stress 9.167412e-05 
... Procrustes: rmse 0.1879636  max resid 0.2853971 
Run 48 stress 7.957956e-05 
... Procrustes: rmse 0.03438225  max resid 0.06038609 
Run 49 stress 0 
... Procrustes: rmse 0.1340051  max resid 0.2204579 
Run 50 stress 0 
... Procrustes: rmse 0.2149505  max resid 0.2891899 
*** No convergence -- monoMDS stopping criteria:
     4: no. of iterations >= maxit
    38: stress < smin
     4: stress ratio > sratmax
     4: scale factor of the gradient < sfgrmin
stress is (nearly) zero: you may have insufficient data
Run 0 stress 0 
Run 1 stress 0.2181459 
Run 2 stress 0.2672326 
Run 3 stress 0 
... Procrustes: rmse 0.1706527  max resid 0.2472902 
Run 4 stress 0 
... Procrustes: rmse 0.163524  max resid 0.2407503 
Run 5 stress 0.2143661 
Run 6 stress 0 
... Procrustes: rmse 0.192329  max resid 0.2568778 
Run 7 stress 0 
... Procrustes: rmse 0.1772413  max resid 0.2274027 
Run 8 stress 9.518459e-05 
... Procrustes: rmse 0.2217095  max resid 0.3941604 
Run 9 stress 0.1470313 
Run 10 stress 0.276137 
Run 11 stress 0 
... Procrustes: rmse 0.1622381  max resid 0.2364686 
Run 12 stress 0 
... Procrustes: rmse 0.1314665  max resid 0.1818057 
Run 13 stress 0 
... Procrustes: rmse 0.1467775  max resid 0.1923097 
Run 14 stress 6.216642e-05 
... Procrustes: rmse 0.2193254  max resid 0.3901086 
Run 15 stress 0 
... Procrustes: rmse 0.1293252  max resid 0.2350656 
Run 16 stress 9.635216e-05 
... Procrustes: rmse 0.170729  max resid 0.284366 
Run 17 stress 0 
... Procrustes: rmse 0.1651769  max resid 0.2469877 
Run 18 stress 3.241269e-05 
... Procrustes: rmse 0.1437676  max resid 0.1771954 
Run 19 stress 0 
... Procrustes: rmse 0.1572113  max resid 0.1960299 
Run 20 stress 0 
... Procrustes: rmse 0.1458955  max resid 0.2260915 
Run 21 stress 0.1470313 
Run 22 stress 0 
... Procrustes: rmse 0.1599721  max resid 0.2298241 
Run 23 stress 0.1470313 
Run 24 stress 9.5205e-05 
... Procrustes: rmse 0.1277011  max resid 0.2292867 
Run 25 stress 0.2143661 
Run 26 stress 0.2181459 
Run 27 stress 0 
... Procrustes: rmse 0.1988506  max resid 0.3485836 
Run 28 stress 0.2761346 
Run 29 stress 0 
... Procrustes: rmse 0.1389998  max resid 0.1856175 
Run 30 stress 0 
... Procrustes: rmse 0.1415347  max resid 0.2085836 
Run 31 stress 0 
... Procrustes: rmse 0.08130354  max resid 0.133839 
Run 32 stress 0 
... Procrustes: rmse 0.160239  max resid 0.268081 
Run 33 stress 0.2761341 
Run 34 stress 0 
... Procrustes: rmse 0.1419449  max resid 0.1854868 
Run 35 stress 0 
... Procrustes: rmse 0.09363463  max resid 0.124746 
Run 36 stress 0.2143661 
Run 37 stress 0 
... Procrustes: rmse 0.1472885  max resid 0.1981838 
Run 38 stress 0 
... Procrustes: rmse 0.1518164  max resid 0.2216571 
Run 39 stress 0 
... Procrustes: rmse 0.1489788  max resid 0.2078257 
Run 40 stress 9.060784e-05 
... Procrustes: rmse 0.1442697  max resid 0.2085266 
Run 41 stress 8.595739e-05 
... Procrustes: rmse 0.177837  max resid 0.213702 
Run 42 stress 5.485652e-05 
... Procrustes: rmse 0.2004741  max resid 0.2437479 
Run 43 stress 0 
... Procrustes: rmse 0.145018  max resid 0.1997814 
Run 44 stress 0 
... Procrustes: rmse 0.1634364  max resid 0.2310717 
Run 45 stress 9.019576e-05 
... Procrustes: rmse 0.1633155  max resid 0.2125998 
Run 46 stress 0 
... Procrustes: rmse 0.2018461  max resid 0.2491446 
Run 47 stress 0 
... Procrustes: rmse 0.1633162  max resid 0.2392174 
Run 48 stress 0 
... Procrustes: rmse 0.1735698  max resid 0.2286069 
Run 49 stress 0.2280378 
Run 50 stress 0 
... Procrustes: rmse 0.1229451  max resid 0.1979459 
*** No convergence -- monoMDS stopping criteria:
    37: stress < smin
     8: stress ratio > sratmax
     5: scale factor of the gradient < sfgrmin

'csv_outputs/bray_dissimilar/mockfeeds' already exists'nperm' >= set of all permutations: complete enumeration.
Set of permutations < 'minperm'. Generating entire set.
Run 0 stress 8.331396e-05 
Run 1 stress 0.2143661 
Run 2 stress 0.2269841 
Run 3 stress 6.487667e-05 
... New best solution
... Procrustes: rmse 0.08939749  max resid 0.1124175 
Run 4 stress 9.788692e-05 
... Procrustes: rmse 0.09199573  max resid 0.1982159 
Run 5 stress 9.371137e-05 
... Procrustes: rmse 0.1791542  max resid 0.2720575 
Run 6 stress 0.2269841 
Run 7 stress 7.936958e-05 
... Procrustes: rmse 0.09203145  max resid 0.1913289 
Run 8 stress 8.831308e-05 
... Procrustes: rmse 0.2081254  max resid 0.3341102 
Run 9 stress 0.2680414 
Run 10 stress 9.919535e-05 
... Procrustes: rmse 0.09120056  max resid 0.1948101 
Run 11 stress 8.86129e-05 
... Procrustes: rmse 0.1834003  max resid 0.2830286 
Run 12 stress 0 
... New best solution
... Procrustes: rmse 0.1773722  max resid 0.2883808 
Run 13 stress 9.900996e-05 
... Procrustes: rmse 0.07657583  max resid 0.1235298 
Run 14 stress 0 
... Procrustes: rmse 0.1853513  max resid 0.3387926 
Run 15 stress 9.021276e-05 
... Procrustes: rmse 0.06294959  max resid 0.07786125 
Run 16 stress 1.330608e-06 
... Procrustes: rmse 0.1460244  max resid 0.2544885 
Run 17 stress 9.19803e-05 
... Procrustes: rmse 0.07257653  max resid 0.1008073 
Run 18 stress 0 
... Procrustes: rmse 0.1464016  max resid 0.2525666 
Run 19 stress 8.532005e-05 
... Procrustes: rmse 0.1496782  max resid 0.2761175 
Run 20 stress 0 
... Procrustes: rmse 0.1795446  max resid 0.3025875 
Run 21 stress 0.2269841 
Run 22 stress 0 
... Procrustes: rmse 0.08708322  max resid 0.1248659 
Run 23 stress 0 
... Procrustes: rmse 0.06197543  max resid 0.09957178 
Run 24 stress 8.35669e-05 
... Procrustes: rmse 0.170691  max resid 0.2848675 
Run 25 stress 0 
... Procrustes: rmse 0.04580526  max resid 0.07458275 
Run 26 stress 0.2673072 
Run 27 stress 0 
... Procrustes: rmse 0.1324469  max resid 0.262764 
Run 28 stress 9.937059e-05 
... Procrustes: rmse 0.13472  max resid 0.2629956 
Run 29 stress 0.2143661 
Run 30 stress 0.2269841 
Run 31 stress 0 
... Procrustes: rmse 0.06346933  max resid 0.1089092 
Run 32 stress 0 
... Procrustes: rmse 0.1805905  max resid 0.3533108 
Run 33 stress 0.2269849 
Run 34 stress 6.446752e-05 
... Procrustes: rmse 0.05841119  max resid 0.1013562 
Run 35 stress 4.001065e-05 
... Procrustes: rmse 0.05248738  max resid 0.080618 
Run 36 stress 9.288712e-05 
... Procrustes: rmse 0.06909143  max resid 0.08507696 
Run 37 stress 0 
... Procrustes: rmse 0.160548  max resid 0.2066414 
Run 38 stress 0.2143661 
Run 39 stress 8.740246e-05 
... Procrustes: rmse 0.156384  max resid 0.2623792 
Run 40 stress 0 
... Procrustes: rmse 0.08440196  max resid 0.1253443 
Run 41 stress 0 
... Procrustes: rmse 0.1668615  max resid 0.2776859 
Run 42 stress 9.611301e-05 
... Procrustes: rmse 0.08661236  max resid 0.1321455 
Run 43 stress 9.462554e-05 
... Procrustes: rmse 0.1493892  max resid 0.2782459 
Run 44 stress 0 
... Procrustes: rmse 0.1461522  max resid 0.2346507 
Run 45 stress 0 
... Procrustes: rmse 0.09250051  max resid 0.1396608 
Run 46 stress 0 
... Procrustes: rmse 0.09637135  max resid 0.1429823 
Run 47 stress 0 
... Procrustes: rmse 0.1224828  max resid 0.224107 
Run 48 stress 0 
... Procrustes: rmse 0.09505105  max resid 0.1433963 
Run 49 stress 9.677961e-05 
... Procrustes: rmse 0.149219  max resid 0.2381071 
Run 50 stress 0 
... Procrustes: rmse 0.1813549  max resid 0.297632 
*** No convergence -- monoMDS stopping criteria:
    40: stress < smin
     6: stress ratio > sratmax
     4: scale factor of the gradient < sfgrmin
stress is (nearly) zero: you may have insufficient data

'csv_outputs/bray_dissimilar/mockfeeds' already exists'nperm' >= set of all permutations: complete enumeration.
Set of permutations < 'minperm'. Generating entire set.
Run 0 stress 0.0003381618 
Run 1 stress 0.1557467 
Run 2 stress 9.845105e-05 
... New best solution
... Procrustes: rmse 0.1048254  max resid 0.1864059 
Run 3 stress 9.19975e-05 
... New best solution
... Procrustes: rmse 0.02914148  max resid 0.04312212 
Run 4 stress 0.1557467 
Run 5 stress 2.725825e-05 
... New best solution
... Procrustes: rmse 0.03067527  max resid 0.04405784 
Run 6 stress 0.2269841 
Run 7 stress 0.0001049999 
... Procrustes: rmse 0.15985  max resid 0.2605553 
Run 8 stress 3.537058e-05 
... Procrustes: rmse 0.2119709  max resid 0.4111482 
Run 9 stress 0.2673072 
Run 10 stress 0.0005377419 
Run 11 stress 0.2405176 
Run 12 stress 6.40736e-05 
... Procrustes: rmse 0.2040217  max resid 0.401824 
Run 13 stress 7.967293e-05 
... Procrustes: rmse 0.2432073  max resid 0.4462463 
Run 14 stress 8.66504e-05 
... Procrustes: rmse 0.2432139  max resid 0.4462532 
Run 15 stress 2.87675e-12 
... New best solution
... Procrustes: rmse 0.2064273  max resid 0.4060603 
Run 16 stress 9.567279e-05 
... Procrustes: rmse 0.1090861  max resid 0.2245351 
Run 17 stress 9.953336e-05 
... Procrustes: rmse 0.212252  max resid 0.3884891 
Run 18 stress 0.0005355913 
Run 19 stress 9.724507e-05 
... Procrustes: rmse 0.0983149  max resid 0.2151959 
Run 20 stress 0.1557467 
Run 21 stress 0.0003968548 
... Procrustes: rmse 0.03623477  max resid 0.06199298 
Run 22 stress 9.713423e-05 
... Procrustes: rmse 0.05652115  max resid 0.07520578 
Run 23 stress 0.2537798 
Run 24 stress 8.14767e-05 
... Procrustes: rmse 0.1563267  max resid 0.3098543 
Run 25 stress 9.830106e-05 
... Procrustes: rmse 0.05770281  max resid 0.07750037 
Run 26 stress 0.2405176 
Run 27 stress 8.950909e-05 
... Procrustes: rmse 0.01268243  max resid 0.02263129 
Run 28 stress 9.819799e-05 
... Procrustes: rmse 0.2010997  max resid 0.3737692 
Run 29 stress 0.1557467 
Run 30 stress 9.675285e-05 
... Procrustes: rmse 0.1825355  max resid 0.3463517 
Run 31 stress 0.0002258919 
... Procrustes: rmse 0.05028445  max resid 0.1036282 
Run 32 stress 9.974731e-05 
... Procrustes: rmse 0.0320083  max resid 0.04495142 
Run 33 stress 0.276136 
Run 34 stress 9.044341e-05 
... Procrustes: rmse 0.03592827  max resid 0.04898544 
Run 35 stress 1.006688e-05 
... Procrustes: rmse 0.01824777  max resid 0.02534925 
Run 36 stress 9.165075e-12 
... Procrustes: rmse 0.009463528  max resid 0.01680075 
Run 37 stress 0.2761343 
Run 38 stress 0.1557467 
Run 39 stress 8.299773e-05 
... Procrustes: rmse 0.1537103  max resid 0.3094937 
Run 40 stress 8.708343e-07 
... Procrustes: rmse 0.004627223  max resid 0.0065775 
... Similar to previous best
*** Solution reached
stress is (nearly) zero: you may have insufficient data

[[1]]
[[1]][[1]]
[[1]][[1]]$x
 [1] 0.13698607 0.09966843 0.10699619 0.10826388 0.01901694 0.10159167 0.09617633 0.09417291
 [9] 0.12464564 0.01529514 0.01598311 0.09191305 0.01019489 0.10127348 0.10211705

[[1]][[1]]$y
 [1] 0.260924603 0.187600658 0.204085475 0.206342473 0.024133760 0.193181171 0.183124784
 [8] 0.179406789 0.237279340 0.020018432 0.024130221 0.176253804 0.004544048 0.191386671
[15] 0.193227465

[[1]][[1]]$yf
 [1] 0.260924603 0.187600658 0.204085475 0.206342473 0.024133760 0.193181171 0.183124784
 [8] 0.179406789 0.237279340 0.020018432 0.024130221 0.176253804 0.004544048 0.191386671
[15] 0.193227465


[[1]][[2]]


[[2]]
[[2]][[1]]
[[2]][[1]]$x
 [1] 0.011106264 0.010129804 0.103112045 0.105659264 0.112632087 0.008494632 0.107304247
 [8] 0.110143755 0.117596064 0.104360784 0.106884229 0.114294945 0.010861103 0.012996968
[15] 0.011125930

[[2]][[1]]$y
 [1] 0.014273185 0.007961262 0.200991368 0.204951528 0.222906835 0.007549471 0.206920319
 [8] 0.211556266 0.229974438 0.201190970 0.205578041 0.223837116 0.011680656 0.029612355
[15] 0.019884124

[[2]][[1]]$yf
 [1] 0.014273185 0.007961262 0.200991368 0.204951528 0.222906835 0.007549471 0.206920319
 [8] 0.211556266 0.229974438 0.201190970 0.205578041 0.223837116 0.011680656 0.029612355
[15] 0.019884124


[[2]][[2]]


[[3]]
[[3]][[1]]
[[3]][[1]]$x
 [1] 0.007792775 0.027989307 0.110738757 0.137087174 0.097747860 0.030930024 0.114437739
 [8] 0.140806467 0.100411856 0.086553516 0.111921863 0.082383272 0.030778463 0.029183971
[15] 0.052960942

[[3]][[1]]$y
 [1] 0.03395793 0.08266693 0.23131322 0.29755970 0.17818379 0.11542778 0.25502878 0.31162632
 [9] 0.19400014 0.16553479 0.25297880 0.13859155 0.11203496 0.08370713 0.11952742

[[3]][[1]]$yf
 [1] 0.03395793 0.08266693 0.23131322 0.29755970 0.17818379 0.11542778 0.25502878 0.31162632
 [9] 0.19400014 0.16553479 0.25297880 0.13859155 0.11203496 0.08370713 0.11952742


[[3]][[2]]


[[4]]
[[4]][[1]]
[[4]][[1]]$x
 [1] 0.02464158 0.13261474 0.18207265 0.25791915 0.21853437 0.13131404 0.18562618 0.26933494
 [9] 0.21992670 0.11080077 0.18085388 0.15162022 0.10597322 0.09767366 0.18919575

[[4]][[1]]$y
 [1] 2.301506e-11 1.982352e-01 3.516852e-01 4.626262e-01 4.022252e-01 1.982352e-01
 [7] 3.516852e-01 4.626262e-01 4.022252e-01 1.872363e-01 3.504114e-01 2.048951e-01
[13] 1.852000e-01 1.848667e-01 3.596816e-01

[[4]][[1]]$yf
 [1] 2.301506e-11 1.982352e-01 3.516852e-01 4.626262e-01 4.022252e-01 1.982352e-01
 [7] 3.516852e-01 4.626262e-01 4.022252e-01 1.872363e-01 3.504114e-01 2.048951e-01
[13] 1.852000e-01 1.848667e-01 3.596816e-01


[[4]][[2]]

# analyze sample F1_2
lapply(locs, bray_nmds_mock_feed, sodm_filtered_df = mock_feed_sodm_asvs_removed_dataframe, site = "F1_2_")
'csv_outputs/bray_dissimilar/mockfeeds' already exists'nperm' >= set of all permutations: complete enumeration.
Set of permutations < 'minperm'. Generating entire set.
Run 0 stress 0 
Run 1 stress 0 
... Procrustes: rmse 0.1223218  max resid 0.1656872 
Run 2 stress 7.072465e-05 
... Procrustes: rmse 0.2508951  max resid 0.3448217 
Run 3 stress 0 
... Procrustes: rmse 0.0792535  max resid 0.1144785 
Run 4 stress 0 
... Procrustes: rmse 0.1722152  max resid 0.2352139 
Run 5 stress 9.521242e-05 
... Procrustes: rmse 0.2299656  max resid 0.3286579 
Run 6 stress 2.267983e-05 
... Procrustes: rmse 0.248738  max resid 0.3401303 
Run 7 stress 2.594614e-05 
... Procrustes: rmse 0.08292225  max resid 0.1291515 
Run 8 stress 7.608151e-05 
... Procrustes: rmse 0.2663827  max resid 0.3650842 
Run 9 stress 0 
... Procrustes: rmse 0.1848908  max resid 0.2604806 
Run 10 stress 0 
... Procrustes: rmse 0.1878001  max resid 0.2516045 
Run 11 stress 7.076838e-05 
... Procrustes: rmse 0.1984967  max resid 0.2830463 
Run 12 stress 0 
... Procrustes: rmse 0.2353047  max resid 0.3226877 
Run 13 stress 9.295404e-05 
... Procrustes: rmse 0.07587773  max resid 0.1020073 
Run 14 stress 9.858445e-05 
... Procrustes: rmse 0.1805886  max resid 0.2517475 
Run 15 stress 9.609867e-05 
... Procrustes: rmse 0.2663965  max resid 0.3650819 
Run 16 stress 9.278764e-05 
... Procrustes: rmse 0.2333222  max resid 0.3187146 
Run 17 stress 9.99939e-05 
... Procrustes: rmse 0.1785587  max resid 0.2294347 
Run 18 stress 0 
... Procrustes: rmse 0.1024366  max resid 0.1462867 
Run 19 stress 0 
... Procrustes: rmse 0.1157086  max resid 0.1819015 
Run 20 stress 0 
... Procrustes: rmse 0.1243144  max resid 0.1663818 
Run 21 stress 5.669388e-05 
... Procrustes: rmse 0.2658425  max resid 0.3644043 
Run 22 stress 0 
... Procrustes: rmse 0.06761828  max resid 0.1060347 
Run 23 stress 8.752271e-05 
... Procrustes: rmse 0.2270201  max resid 0.3203358 
Run 24 stress 0 
... Procrustes: rmse 0.02635104  max resid 0.03858882 
Run 25 stress 9.720708e-05 
... Procrustes: rmse 0.2171371  max resid 0.3050963 
Run 26 stress 6.296699e-05 
... Procrustes: rmse 0.2532506  max resid 0.3495244 
Run 27 stress 0 
... Procrustes: rmse 0.1516025  max resid 0.2168951 
Run 28 stress 0 
... Procrustes: rmse 0.2212991  max resid 0.3060809 
Run 29 stress 0 
... Procrustes: rmse 0.2117351  max resid 0.2917023 
Run 30 stress 7.599806e-05 
... Procrustes: rmse 0.2628509  max resid 0.3599699 
Run 31 stress 1.231121e-05 
... Procrustes: rmse 0.1028224  max resid 0.1519504 
Run 32 stress 8.82991e-05 
... Procrustes: rmse 0.0966383  max resid 0.1209726 
Run 33 stress 0 
... Procrustes: rmse 0.2169812  max resid 0.2993104 
Run 34 stress 0 
... Procrustes: rmse 0.08984891  max resid 0.1436508 
Run 35 stress 9.537374e-05 
... Procrustes: rmse 0.1208359  max resid 0.1603184 
Run 36 stress 0 
... Procrustes: rmse 0.23336  max resid 0.3234995 
Run 37 stress 9.970693e-05 
... Procrustes: rmse 0.2215751  max resid 0.3167446 
Run 38 stress 9.653247e-05 
... Procrustes: rmse 0.1720133  max resid 0.23857 
Run 39 stress 0 
... Procrustes: rmse 0.1055798  max resid 0.1563873 
Run 40 stress 6.664626e-05 
... Procrustes: rmse 0.2134482  max resid 0.3029879 
Run 41 stress 9.112601e-05 
... Procrustes: rmse 0.1787802  max resid 0.254843 
Run 42 stress 0 
... Procrustes: rmse 0.1204302  max resid 0.1471806 
Run 43 stress 0 
... Procrustes: rmse 0.101409  max resid 0.146566 
Run 44 stress 0 
... Procrustes: rmse 0.07364291  max resid 0.1044094 
Run 45 stress 0 
... Procrustes: rmse 0.1289976  max resid 0.1885612 
Run 46 stress 8.911955e-05 
... Procrustes: rmse 0.2472635  max resid 0.338419 
Run 47 stress 9.568779e-05 
... Procrustes: rmse 0.1485338  max resid 0.2108878 
Run 48 stress 0 
... Procrustes: rmse 0.1369993  max resid 0.1915395 
Run 49 stress 9.450226e-05 
... Procrustes: rmse 0.184388  max resid 0.2626905 
Run 50 stress 0 
... Procrustes: rmse 0.1418683  max resid 0.1911597 
*** No convergence -- monoMDS stopping criteria:
    50: stress < smin
stress is (nearly) zero: you may have insufficient data
Run 0 stress 2.124151e-05 
Run 1 stress 0 
... New best solution
... Procrustes: rmse 0.157537  max resid 0.1820812 
Run 2 stress 0.2672679 
Run 3 stress 2.326337e-05 
... Procrustes: rmse 0.1968781  max resid 0.2903448 
Run 4 stress 0.2181459 
Run 5 stress 0 
... Procrustes: rmse 0.1989075  max resid 0.2604973 
Run 6 stress 2.895186e-05 
... Procrustes: rmse 0.1189694  max resid 0.1580015 
Run 7 stress 0 
... Procrustes: rmse 0.1004432  max resid 0.1273505 
Run 8 stress 0.1557467 
Run 9 stress 0 
... Procrustes: rmse 0.06913063  max resid 0.1308691 
Run 10 stress 0 
... Procrustes: rmse 0.1227099  max resid 0.1738979 
Run 11 stress 0 
... Procrustes: rmse 0.1553157  max resid 0.2218817 
Run 12 stress 0.1557467 
Run 13 stress 0 
... Procrustes: rmse 0.09654797  max resid 0.1534925 
Run 14 stress 0 
... Procrustes: rmse 0.06960064  max resid 0.1143846 
Run 15 stress 0.1557467 
Run 16 stress 0 
... Procrustes: rmse 0.1095223  max resid 0.1417771 
Run 17 stress 0 
... Procrustes: rmse 0.1562131  max resid 0.1989529 
Run 18 stress 0 
... Procrustes: rmse 0.1710129  max resid 0.2870675 
Run 19 stress 0 
... Procrustes: rmse 0.07739966  max resid 0.1129684 
Run 20 stress 0 
... Procrustes: rmse 0.245458  max resid 0.317773 
Run 21 stress 0 
... Procrustes: rmse 0.1663953  max resid 0.2197683 
Run 22 stress 0 
... Procrustes: rmse 0.1121602  max resid 0.1511245 
Run 23 stress 0 
... Procrustes: rmse 0.1090136  max resid 0.1645137 
Run 24 stress 9.515995e-05 
... Procrustes: rmse 0.2035066  max resid 0.2618318 
Run 25 stress 0 
... Procrustes: rmse 0.06575861  max resid 0.08991442 
Run 26 stress 0 
... Procrustes: rmse 0.07866976  max resid 0.1228012 
Run 27 stress 4.604018e-05 
... Procrustes: rmse 0.08763106  max resid 0.1560758 
Run 28 stress 0.2181459 
Run 29 stress 0 
... Procrustes: rmse 0.1129685  max resid 0.1687105 
Run 30 stress 8.9267e-05 
... Procrustes: rmse 0.1391779  max resid 0.2695348 
Run 31 stress 0 
... Procrustes: rmse 0.1337685  max resid 0.1803485 
Run 32 stress 0 
... Procrustes: rmse 0.1234044  max resid 0.1759336 
Run 33 stress 9.15148e-05 
... Procrustes: rmse 0.1537131  max resid 0.2566823 
Run 34 stress 5.096189e-05 
... Procrustes: rmse 0.1552274  max resid 0.1950005 
Run 35 stress 0 
... Procrustes: rmse 0.08441157  max resid 0.1170539 
Run 36 stress 0.1557467 
Run 37 stress 0 
... Procrustes: rmse 0.1174666  max resid 0.167026 
Run 38 stress 0 
... Procrustes: rmse 0.1370138  max resid 0.1760105 
Run 39 stress 0 
... Procrustes: rmse 0.1448919  max resid 0.1990777 
Run 40 stress 0.1557467 
Run 41 stress 0 
... Procrustes: rmse 0.1035365  max resid 0.1661832 
Run 42 stress 0 
... Procrustes: rmse 0.1670909  max resid 0.2460737 
Run 43 stress 0 
... Procrustes: rmse 0.1858107  max resid 0.2598215 
Run 44 stress 0 
... Procrustes: rmse 0.1935573  max resid 0.3249048 
Run 45 stress 0 
... Procrustes: rmse 0.1377805  max resid 0.2227059 
Run 46 stress 0.1557467 
Run 47 stress 0 
... Procrustes: rmse 0.06953413  max resid 0.1013176 
Run 48 stress 2.185571e-06 
... Procrustes: rmse 0.1280379  max resid 0.1906299 
Run 49 stress 0 
... Procrustes: rmse 0.2123503  max resid 0.3384559 
Run 50 stress 0 
... Procrustes: rmse 0.1617054  max resid 0.2546631 
*** No convergence -- monoMDS stopping criteria:
    41: stress < smin
     4: stress ratio > sratmax
     5: scale factor of the gradient < sfgrmin

'csv_outputs/bray_dissimilar/mockfeeds' already exists'nperm' >= set of all permutations: complete enumeration.
Set of permutations < 'minperm'. Generating entire set.
Run 0 stress 7.690157e-05 
Run 1 stress 9.146088e-05 
... Procrustes: rmse 0.1415001  max resid 0.1763404 
Run 2 stress 0.2672326 
Run 3 stress 5.403948e-05 
... New best solution
... Procrustes: rmse 0.1011135  max resid 0.1415481 
Run 4 stress 0.2181459 
Run 5 stress 0 
... New best solution
... Procrustes: rmse 0.07776228  max resid 0.1018469 
Run 6 stress 9.884376e-05 
... Procrustes: rmse 0.1517016  max resid 0.2350077 
Run 7 stress 0 
... Procrustes: rmse 0.1475991  max resid 0.2231857 
Run 8 stress 0.2181459 
Run 9 stress 9.661122e-05 
... Procrustes: rmse 0.1461225  max resid 0.2112905 
Run 10 stress 0 
... Procrustes: rmse 0.1872038  max resid 0.357011 
Run 11 stress 9.944485e-05 
... Procrustes: rmse 0.1335075  max resid 0.1685597 
Run 12 stress 0.2181459 
Run 13 stress 0 
... Procrustes: rmse 0.1499212  max resid 0.2717162 
Run 14 stress 9.552391e-05 
... Procrustes: rmse 0.1356566  max resid 0.1653038 
Run 15 stress 0 
... Procrustes: rmse 0.1651368  max resid 0.296857 
Run 16 stress 9.842682e-05 
... Procrustes: rmse 0.1155894  max resid 0.1949442 
Run 17 stress 0 
... Procrustes: rmse 0.1838935  max resid 0.3036845 
Run 18 stress 0 
... Procrustes: rmse 0.147089  max resid 0.2688188 
Run 19 stress 9.382864e-05 
... Procrustes: rmse 0.1224032  max resid 0.1626796 
Run 20 stress 0 
... Procrustes: rmse 0.152046  max resid 0.2392613 
Run 21 stress 9.070282e-05 
... Procrustes: rmse 0.1424178  max resid 0.2121383 
Run 22 stress 9.709145e-05 
... Procrustes: rmse 0.1396264  max resid 0.2046795 
Run 23 stress 1.876887e-05 
... Procrustes: rmse 0.06508739  max resid 0.09650626 
Run 24 stress 9.572346e-05 
... Procrustes: rmse 0.1028844  max resid 0.1323138 
Run 25 stress 6.913225e-05 
... Procrustes: rmse 0.1617473  max resid 0.2317607 
Run 26 stress 0 
... Procrustes: rmse 0.1152998  max resid 0.1599585 
Run 27 stress 6.65981e-05 
... Procrustes: rmse 0.08531527  max resid 0.114115 
Run 28 stress 7.315397e-05 
... Procrustes: rmse 0.1425555  max resid 0.2120054 
Run 29 stress 9.803795e-05 
... Procrustes: rmse 0.1453514  max resid 0.2374238 
Run 30 stress 8.976881e-05 
... Procrustes: rmse 0.07811154  max resid 0.09951727 
Run 31 stress 0 
... Procrustes: rmse 0.1090569  max resid 0.2016708 
Run 32 stress 2.774429e-05 
... Procrustes: rmse 0.03809068  max resid 0.06023713 
Run 33 stress 0 
... Procrustes: rmse 0.1406218  max resid 0.2167305 
Run 34 stress 0 
... Procrustes: rmse 0.1138822  max resid 0.2022683 
Run 35 stress 0 
... Procrustes: rmse 0.1485088  max resid 0.2909942 
Run 36 stress 0 
... Procrustes: rmse 0.2068267  max resid 0.3509717 
Run 37 stress 9.81161e-05 
... Procrustes: rmse 0.1136406  max resid 0.154546 
Run 38 stress 8.929985e-05 
... Procrustes: rmse 0.1602806  max resid 0.2425274 
Run 39 stress 9.327513e-05 
... Procrustes: rmse 0.06010741  max resid 0.09688332 
Run 40 stress 0.2130992 
Run 41 stress 0 
... Procrustes: rmse 0.1728767  max resid 0.2812426 
Run 42 stress 0.1557467 
Run 43 stress 9.003367e-05 
... Procrustes: rmse 0.09705937  max resid 0.1231281 
Run 44 stress 0 
... Procrustes: rmse 0.0784769  max resid 0.1002845 
Run 45 stress 0 
... Procrustes: rmse 0.1765949  max resid 0.3360861 
Run 46 stress 0.1557467 
Run 47 stress 8.141485e-05 
... Procrustes: rmse 0.03671525  max resid 0.0492191 
Run 48 stress 8.236852e-05 
... Procrustes: rmse 0.1332011  max resid 0.2059865 
Run 49 stress 0 
... Procrustes: rmse 0.1164019  max resid 0.197308 
Run 50 stress 9.072801e-05 
... Procrustes: rmse 0.08213255  max resid 0.1202882 
*** No convergence -- monoMDS stopping criteria:
    43: stress < smin
     2: stress ratio > sratmax
     5: scale factor of the gradient < sfgrmin
stress is (nearly) zero: you may have insufficient data

'csv_outputs/bray_dissimilar/mockfeeds' already exists'nperm' >= set of all permutations: complete enumeration.
Set of permutations < 'minperm'. Generating entire set.
Run 0 stress 8.283428e-05 
Run 1 stress 5.053448e-05 
... New best solution
... Procrustes: rmse 0.1922255  max resid 0.2868384 
Run 2 stress 4.103509e-05 
... New best solution
... Procrustes: rmse 0.08844274  max resid 0.1416263 
Run 3 stress 6.233269e-05 
... Procrustes: rmse 0.2923098  max resid 0.5834878 
Run 4 stress 8.698547e-05 
... Procrustes: rmse 0.07897695  max resid 0.1104613 
Run 5 stress 0.0002641342 
... Procrustes: rmse 0.1499903  max resid 0.2000758 
Run 6 stress 9.342291e-05 
... Procrustes: rmse 0.1526383  max resid 0.2268521 
Run 7 stress 6.822434e-05 
... Procrustes: rmse 0.00930892  max resid 0.01528143 
Run 8 stress 8.709558e-05 
... Procrustes: rmse 0.1643062  max resid 0.2493343 
Run 9 stress 9.432742e-05 
... Procrustes: rmse 0.2039125  max resid 0.3340389 
Run 10 stress 5.844301e-05 
... Procrustes: rmse 0.1747382  max resid 0.3067221 
Run 11 stress 9.479429e-05 
... Procrustes: rmse 0.2304286  max resid 0.3665073 
Run 12 stress 1.000118e-05 
... New best solution
... Procrustes: rmse 0.1422626  max resid 0.2404533 
Run 13 stress 9.185907e-05 
... Procrustes: rmse 0.06704519  max resid 0.107192 
Run 14 stress 8.85248e-05 
... Procrustes: rmse 0.07529254  max resid 0.09924686 
Run 15 stress 9.914424e-05 
... Procrustes: rmse 0.05604204  max resid 0.0821208 
Run 16 stress 9.616633e-05 
... Procrustes: rmse 0.2512455  max resid 0.4208675 
Run 17 stress 9.977291e-05 
... Procrustes: rmse 0.23865  max resid 0.4255241 
Run 18 stress 8.79261e-05 
... Procrustes: rmse 0.08351139  max resid 0.1501583 
Run 19 stress 8.982621e-05 
... Procrustes: rmse 0.07555638  max resid 0.1094195 
Run 20 stress 0 
... New best solution
... Procrustes: rmse 0.1506845  max resid 0.2355684 
Run 21 stress 1.97294e-05 
... Procrustes: rmse 0.0875201  max resid 0.1458886 
Run 22 stress 9.106491e-05 
... Procrustes: rmse 0.1151792  max resid 0.1482155 
Run 23 stress 7.758199e-05 
... Procrustes: rmse 0.1405023  max resid 0.1869294 
Run 24 stress 0 
... Procrustes: rmse 0.1561257  max resid 0.2380979 
Run 25 stress 0 
... Procrustes: rmse 0.1113668  max resid 0.1961744 
Run 26 stress 0 
... Procrustes: rmse 0.1376971  max resid 0.1880477 
Run 27 stress 9.97782e-05 
... Procrustes: rmse 0.1220643  max resid 0.169902 
Run 28 stress 9.795589e-05 
... Procrustes: rmse 0.1778349  max resid 0.3706085 
Run 29 stress 0 
... Procrustes: rmse 0.1210496  max resid 0.1725115 
Run 30 stress 9.244629e-05 
... Procrustes: rmse 0.1236686  max resid 0.1605261 
Run 31 stress 8.785011e-05 
... Procrustes: rmse 0.2074715  max resid 0.3033475 
Run 32 stress 9.960447e-05 
... Procrustes: rmse 0.1992931  max resid 0.2934866 
Run 33 stress 9.658745e-05 
... Procrustes: rmse 0.1970808  max resid 0.3035161 
Run 34 stress 2.344357e-05 
... Procrustes: rmse 0.1839445  max resid 0.2925193 
Run 35 stress 0 
... Procrustes: rmse 0.1450726  max resid 0.1993992 
Run 36 stress 7.866307e-05 
... Procrustes: rmse 0.1696241  max resid 0.2543011 
Run 37 stress 1.002386e-05 
... Procrustes: rmse 0.2107818  max resid 0.3641185 
Run 38 stress 0 
... Procrustes: rmse 0.1925185  max resid 0.3438176 
Run 39 stress 0.0003674189 
... Procrustes: rmse 0.1415747  max resid 0.2053768 
Run 40 stress 4.748581e-05 
... Procrustes: rmse 0.2080998  max resid 0.3595177 
Run 41 stress 9.761551e-05 
... Procrustes: rmse 0.1485312  max resid 0.2058994 
Run 42 stress 9.653015e-05 
... Procrustes: rmse 0.2155408  max resid 0.3141755 
Run 43 stress 9.827622e-05 
... Procrustes: rmse 0.1938504  max resid 0.3872057 
Run 44 stress 9.879833e-05 
... Procrustes: rmse 0.1387625  max resid 0.1952533 
Run 45 stress 9.581024e-05 
... Procrustes: rmse 0.2254252  max resid 0.3182791 
Run 46 stress 0 
... Procrustes: rmse 0.166148  max resid 0.2369382 
Run 47 stress 0 
... Procrustes: rmse 0.1029269  max resid 0.1752032 
Run 48 stress 5.557643e-05 
... Procrustes: rmse 0.1230135  max resid 0.1761402 
Run 49 stress 9.470078e-05 
... Procrustes: rmse 0.1124555  max resid 0.1502745 
Run 50 stress 9.891358e-05 
... Procrustes: rmse 0.1378317  max resid 0.1765846 
*** No convergence -- monoMDS stopping criteria:
     2: no. of iterations >= maxit
    48: stress < smin
stress is (nearly) zero: you may have insufficient data

[[1]]
[[1]][[1]]
[[1]][[1]]$x
 [1] 0.01726958 0.15581134 0.13147161 0.13253152 0.13572321 0.15194484 0.13535630 0.13626957
 [9] 0.13917859 0.22884030 0.21698238 0.22878422 0.02160788 0.02158823 0.02048543

[[1]][[1]]$y
 [1] 0.01020047 0.29896654 0.24744217 0.25458135 0.26089179 0.29132468 0.25614336 0.26246972
 [9] 0.26897552 0.44058375 0.42222387 0.43240206 0.03572964 0.03055534 0.01029507

[[1]][[1]]$yf
 [1] 0.01020047 0.29896654 0.24744217 0.25458135 0.26089179 0.29132468 0.25614336 0.26246972
 [9] 0.26897552 0.44058375 0.42222387 0.43240206 0.03572964 0.03055534 0.01029507


[[1]][[2]]


[[2]]
[[2]][[1]]
[[2]][[1]]$x
 [1] 0.01147500 0.02600497 0.13253819 0.13465471 0.13565457 0.02260174 0.13312275 0.13511137
 [9] 0.13596663 0.14185829 0.14404187 0.14516469 0.01854379 0.02257133 0.02236667

[[2]][[1]]$y
 [1] 0.02187808 0.13623262 0.16095319 0.21033630 0.23620898 0.12830338 0.17555454 0.22308581
 [9] 0.25492757 0.29516355 0.34583188 0.35917942 0.05274279 0.09783240 0.09703298

[[2]][[1]]$yf
 [1] 0.02187808 0.13623262 0.16095319 0.21033630 0.23620898 0.12830338 0.17555454 0.22308581
 [9] 0.25492757 0.29516355 0.34583188 0.35917942 0.05274279 0.09783240 0.09703298


[[2]][[2]]


[[3]]
[[3]][[1]]
[[3]][[1]]$x
 [1] 0.01407066 0.03006718 0.17570586 0.17886640 0.18439056 0.02975746 0.17130494 0.17531223
 [9] 0.17960375 0.18602513 0.18952329 0.19520634 0.01703427 0.02094083 0.01595125

[[3]][[1]]$y
 [1] 0.05546866 0.20631279 0.30115446 0.34739099 0.42809877 0.20318227 0.25843910 0.29706766
 [9] 0.37673420 0.43138862 0.43908097 0.50572827 0.08787990 0.15932259 0.08198425

[[3]][[1]]$yf
 [1] 0.05546866 0.20631279 0.30115446 0.34739099 0.42809877 0.20318227 0.25843910 0.29706766
 [9] 0.37673420 0.43138862 0.43908097 0.50572827 0.08787990 0.15932259 0.08198425


[[3]][[2]]


[[4]]
[[4]][[1]]
[[4]][[1]]$x
 [1] 0.56381918 0.61080106 0.61709803 0.75387552 0.47348778 0.07365421 0.07352797 0.26547630
 [9] 0.15229718 0.01959458 0.27039870 0.20200411 0.26224033 0.20489328 0.31007686

[[4]][[1]]$y
 [1] 1.01461542 1.26889112 1.27517861 1.53062084 0.91038711 0.33630473 0.31910553 0.55271222
 [9] 0.34940444 0.04138279 0.55546217 0.39501444 0.51471766 0.41640377 0.85816245

[[4]][[1]]$yf
 [1] 1.01461542 1.26889112 1.27517861 1.53062084 0.91038711 0.33630473 0.31910553 0.55271222
 [9] 0.34940444 0.04138279 0.55546217 0.39501444 0.51471766 0.41640377 0.85816245


[[4]][[2]]

# analyze sample F1_25
lapply(locs, bray_nmds_mock_feed, sodm_filtered_df = mock_feed_sodm_asvs_removed_dataframe, site = "F1_25")
'csv_outputs/bray_dissimilar/mockfeeds' already exists'nperm' >= set of all permutations: complete enumeration.
Set of permutations < 'minperm'. Generating entire set.
Run 0 stress 9.687844e-05 
Run 1 stress 0.1557467 
Run 2 stress 9.923749e-05 
... Procrustes: rmse 0.1533171  max resid 0.2285749 
Run 3 stress 0.0001119639 
... Procrustes: rmse 0.08191147  max resid 0.148517 
Run 4 stress 8.864365e-05 
... New best solution
... Procrustes: rmse 0.144963  max resid 0.2148241 
Run 5 stress 0.2672977 
Run 6 stress 0.2269841 
Run 7 stress 8.999738e-05 
... Procrustes: rmse 0.1467988  max resid 0.2523924 
Run 8 stress 0.2280378 
Run 9 stress 0.2269843 
Run 10 stress 8.655578e-05 
... New best solution
... Procrustes: rmse 0.1125068  max resid 0.1987212 
Run 11 stress 0.2181459 
Run 12 stress 9.788223e-05 
... Procrustes: rmse 0.0742367  max resid 0.1426694 
Run 13 stress 9.570262e-05 
... Procrustes: rmse 0.1070376  max resid 0.1794512 
Run 14 stress 0.0001993861 
... Procrustes: rmse 0.1517728  max resid 0.2082663 
Run 15 stress 0.2280378 
Run 16 stress 9.743709e-05 
... Procrustes: rmse 0.09235497  max resid 0.14615 
Run 17 stress 7.999889e-05 
... New best solution
... Procrustes: rmse 0.1573976  max resid 0.2225491 
Run 18 stress 3.467416e-06 
... New best solution
... Procrustes: rmse 0.1317174  max resid 0.2237248 
Run 19 stress 7.523051e-05 
... Procrustes: rmse 0.1777496  max resid 0.3632702 
Run 20 stress 9.124949e-05 
... Procrustes: rmse 0.04711426  max resid 0.06562554 
Run 21 stress 9.751295e-05 
... Procrustes: rmse 0.1184699  max resid 0.1904849 
Run 22 stress 0.001139641 
Run 23 stress 9.789778e-05 
... Procrustes: rmse 0.06606032  max resid 0.1170474 
Run 24 stress 6.164918e-05 
... Procrustes: rmse 0.1904947  max resid 0.3499253 
Run 25 stress 0.2673072 
Run 26 stress 5.766115e-05 
... Procrustes: rmse 0.03537994  max resid 0.05763187 
Run 27 stress 9.787711e-05 
... Procrustes: rmse 0.1334064  max resid 0.2417075 
Run 28 stress 0.1557467 
Run 29 stress 0.1557467 
Run 30 stress 0.2673848 
Run 31 stress 9.956824e-05 
... Procrustes: rmse 0.1227267  max resid 0.1897208 
Run 32 stress 9.078131e-05 
... Procrustes: rmse 0.1271666  max resid 0.2293123 
Run 33 stress 5.211457e-05 
... Procrustes: rmse 0.1032831  max resid 0.1645338 
Run 34 stress 7.982201e-05 
... Procrustes: rmse 0.04556295  max resid 0.06692898 
Run 35 stress 9.515436e-05 
... Procrustes: rmse 0.09012572  max resid 0.1428019 
Run 36 stress 0.2269844 
Run 37 stress 9.464142e-05 
... Procrustes: rmse 0.1650476  max resid 0.2698445 
Run 38 stress 0.2672679 
Run 39 stress 9.806596e-05 
... Procrustes: rmse 0.133992  max resid 0.2726458 
Run 40 stress 9.567766e-05 
... Procrustes: rmse 0.1144961  max resid 0.1794957 
Run 41 stress 0.0001243479 
... Procrustes: rmse 0.1413484  max resid 0.2321469 
Run 42 stress 9.129546e-05 
... Procrustes: rmse 0.1007795  max resid 0.1415661 
Run 43 stress 8.906618e-05 
... Procrustes: rmse 0.197313  max resid 0.3598438 
Run 44 stress 0.0003167431 
... Procrustes: rmse 0.1753701  max resid 0.3378403 
Run 45 stress 8.68979e-05 
... Procrustes: rmse 0.06420183  max resid 0.09655708 
Run 46 stress 9.695053e-05 
... Procrustes: rmse 0.09478322  max resid 0.1725051 
Run 47 stress 9.455382e-05 
... Procrustes: rmse 0.1617895  max resid 0.2704003 
Run 48 stress 0.2269842 
Run 49 stress 0.2269841 
Run 50 stress 8.596888e-05 
... Procrustes: rmse 0.184057  max resid 0.3786299 
*** No convergence -- monoMDS stopping criteria:
     5: no. of iterations >= maxit
    30: stress < smin
     8: stress ratio > sratmax
     7: scale factor of the gradient < sfgrmin
stress is (nearly) zero: you may have insufficient data
Run 0 stress 0 
Run 1 stress 0.1970951 
Run 2 stress 8.863024e-05 
... Procrustes: rmse 0.1435982  max resid 0.2352675 
Run 3 stress 0 
... Procrustes: rmse 0.07573411  max resid 0.1322859 
Run 4 stress 0.1967694 
Run 5 stress 0 
... Procrustes: rmse 0.1745504  max resid 0.2421015 
Run 6 stress 0.2673072 
Run 7 stress 0 
... Procrustes: rmse 0.09187165  max resid 0.1294829 
Run 8 stress 0.1557467 
Run 9 stress 0.268042 
Run 10 stress 0.2680416 
Run 11 stress 0 
... Procrustes: rmse 0.1384206  max resid 0.2284591 
Run 12 stress 0.1557467 
Run 13 stress 0 
... Procrustes: rmse 0.1427498  max resid 0.1988049 
Run 14 stress 0.001800982 
Run 15 stress 9.393584e-05 
... Procrustes: rmse 0.1385404  max resid 0.2010457 
Run 16 stress 0 
... Procrustes: rmse 0.1423701  max resid 0.2850375 
Run 17 stress 0 
... Procrustes: rmse 0.141683  max resid 0.230586 
Run 18 stress 0 
... Procrustes: rmse 0.1411673  max resid 0.2245337 
Run 19 stress 7.634129e-05 
... Procrustes: rmse 0.0351002  max resid 0.06229319 
Run 20 stress 8.105708e-05 
... Procrustes: rmse 0.1945288  max resid 0.2835619 
Run 21 stress 0 
... Procrustes: rmse 0.168572  max resid 0.2385113 
Run 22 stress 0.2181459 
Run 23 stress 3.190408e-05 
... Procrustes: rmse 0.1464289  max resid 0.2353091 
Run 24 stress 2.075549e-05 
... Procrustes: rmse 0.1576329  max resid 0.217991 
Run 25 stress 9.794157e-05 
... Procrustes: rmse 0.1410846  max resid 0.2314156 
Run 26 stress 0 
... Procrustes: rmse 0.1513367  max resid 0.2221781 
Run 27 stress 0.001538192 
Run 28 stress 0.1967694 
Run 29 stress 0.2181459 
Run 30 stress 9.716556e-05 
... Procrustes: rmse 0.1598371  max resid 0.2146547 
Run 31 stress 0 
... Procrustes: rmse 0.08348614  max resid 0.1269381 
Run 32 stress 0 
... Procrustes: rmse 0.1540523  max resid 0.2627928 
Run 33 stress 0.2680415 
Run 34 stress 0 
... Procrustes: rmse 0.09358032  max resid 0.1352798 
Run 35 stress 0 
... Procrustes: rmse 0.1373076  max resid 0.2203163 
Run 36 stress 0.1557467 
Run 37 stress 8.116013e-06 
... Procrustes: rmse 0.1423874  max resid 0.2266262 
Run 38 stress 0 
... Procrustes: rmse 0.139295  max resid 0.2282558 
Run 39 stress 0 
... Procrustes: rmse 0.08156026  max resid 0.1277834 
Run 40 stress 9.540915e-05 
... Procrustes: rmse 0.1434018  max resid 0.2426756 
Run 41 stress 0 
... Procrustes: rmse 0.16078  max resid 0.2929022 
Run 42 stress 0.2181459 
Run 43 stress 8.491538e-05 
... Procrustes: rmse 0.1351561  max resid 0.2129919 
Run 44 stress 0 
... Procrustes: rmse 0.1783136  max resid 0.2768127 
Run 45 stress 0.2673072 
Run 46 stress 0.1557467 
Run 47 stress 9.26848e-05 
... Procrustes: rmse 0.1518318  max resid 0.2034258 
Run 48 stress 0.2181459 
Run 49 stress 9.688086e-05 
... Procrustes: rmse 0.1772886  max resid 0.3425121 
Run 50 stress 0 
... Procrustes: rmse 0.09019609  max resid 0.142133 
*** No convergence -- monoMDS stopping criteria:
     2: no. of iterations >= maxit
    32: stress < smin
     7: stress ratio > sratmax
     9: scale factor of the gradient < sfgrmin

'csv_outputs/bray_dissimilar/mockfeeds' already exists'nperm' >= set of all permutations: complete enumeration.
Set of permutations < 'minperm'. Generating entire set.
Run 0 stress 0 
Run 1 stress 0 
... Procrustes: rmse 0.1705458  max resid 0.258408 
Run 2 stress 0.2672326 
Run 3 stress 0 
... Procrustes: rmse 0.157289  max resid 0.2113419 
Run 4 stress 9.415192e-05 
... Procrustes: rmse 0.16422  max resid 0.1964474 
Run 5 stress 0.1557467 
Run 6 stress 0.2269841 
Run 7 stress 0 
... Procrustes: rmse 0.1370493  max resid 0.1880191 
Run 8 stress 0.2130991 
Run 9 stress 5.3319e-05 
... Procrustes: rmse 0.1805194  max resid 0.2833489 
Run 10 stress 0 
... Procrustes: rmse 0.1778136  max resid 0.2268477 
Run 11 stress 0 
... Procrustes: rmse 0.1861077  max resid 0.2705517 
Run 12 stress 0.1557467 
Run 13 stress 0 
... Procrustes: rmse 0.144196  max resid 0.2196323 
Run 14 stress 0 
... Procrustes: rmse 0.1579901  max resid 0.2615369 
Run 15 stress 0.2181459 
Run 16 stress 0 
... Procrustes: rmse 0.1756941  max resid 0.309202 
Run 17 stress 0 
... Procrustes: rmse 0.16738  max resid 0.2239437 
Run 18 stress 0 
... Procrustes: rmse 0.1699554  max resid 0.2485559 
Run 19 stress 0 
... Procrustes: rmse 0.1272678  max resid 0.2034016 
Run 20 stress 0 
... Procrustes: rmse 0.168326  max resid 0.2256897 
Run 21 stress 0 
... Procrustes: rmse 0.1352342  max resid 0.1782558 
Run 22 stress 0 
... Procrustes: rmse 0.1764752  max resid 0.2271915 
Run 23 stress 0 
... Procrustes: rmse 0.1481683  max resid 0.2013022 
Run 24 stress 0 
... Procrustes: rmse 0.1304938  max resid 0.1814899 
Run 25 stress 0 
... Procrustes: rmse 0.1233189  max resid 0.1655978 
Run 26 stress 0 
... Procrustes: rmse 0.2059416  max resid 0.3113155 
Run 27 stress 0 
... Procrustes: rmse 0.2004589  max resid 0.3548216 
Run 28 stress 0.2761338 
Run 29 stress 0 
... Procrustes: rmse 0.1397922  max resid 0.2175155 
Run 30 stress 0.1557467 
Run 31 stress 0 
... Procrustes: rmse 0.0416891  max resid 0.07656757 
Run 32 stress 8.177802e-05 
... Procrustes: rmse 0.176452  max resid 0.2834923 
Run 33 stress 0.2761339 
Run 34 stress 0 
... Procrustes: rmse 0.1464626  max resid 0.1924123 
Run 35 stress 0 
... Procrustes: rmse 0.05062323  max resid 0.09048377 
Run 36 stress 0.1557467 
Run 37 stress 0 
... Procrustes: rmse 0.1389981  max resid 0.1966292 
Run 38 stress 0.2269844 
Run 39 stress 0 
... Procrustes: rmse 0.1639106  max resid 0.2207765 
Run 40 stress 0.213099 
Run 41 stress 0 
... Procrustes: rmse 0.1357025  max resid 0.2083207 
Run 42 stress 3.013413e-06 
... Procrustes: rmse 0.187113  max resid 0.2192378 
Run 43 stress 0 
... Procrustes: rmse 0.1254231  max resid 0.1715368 
Run 44 stress 0 
... Procrustes: rmse 0.1126143  max resid 0.1384301 
Run 45 stress 9.953427e-05 
... Procrustes: rmse 0.1953697  max resid 0.2476744 
Run 46 stress 0 
... Procrustes: rmse 0.1762942  max resid 0.2161173 
Run 47 stress 0 
... Procrustes: rmse 0.1279137  max resid 0.1761318 
Run 48 stress 0.2269841 
Run 49 stress 0.1967694 
Run 50 stress 9.617081e-05 
... Procrustes: rmse 0.14562  max resid 0.1815759 
*** No convergence -- monoMDS stopping criteria:
    36: stress < smin
     8: stress ratio > sratmax
     6: scale factor of the gradient < sfgrmin
stress is (nearly) zero: you may have insufficient data

'csv_outputs/bray_dissimilar/mockfeeds' already exists'nperm' >= set of all permutations: complete enumeration.
Set of permutations < 'minperm'. Generating entire set.
Run 0 stress 3.789846e-05 
Run 1 stress 0 
... New best solution
... Procrustes: rmse 0.1145109  max resid 0.1536262 
Run 2 stress 0 
... Procrustes: rmse 0.07980724  max resid 0.1213707 
Run 3 stress 0.2280383 
Run 4 stress 0.2280379 
Run 5 stress 6.542467e-05 
... Procrustes: rmse 0.1073094  max resid 0.1471331 
Run 6 stress 5.310242e-05 
... Procrustes: rmse 0.099313  max resid 0.1480259 
Run 7 stress 0.2269841 
Run 8 stress 0 
... Procrustes: rmse 0.1251073  max resid 0.1871881 
Run 9 stress 0.1470313 
Run 10 stress 2.422631e-05 
... Procrustes: rmse 0.1746746  max resid 0.2877084 
Run 11 stress 9.933525e-05 
... Procrustes: rmse 0.1284031  max resid 0.1674343 
Run 12 stress 7.507572e-05 
... Procrustes: rmse 0.1084557  max resid 0.1772481 
Run 13 stress 8.795388e-05 
... Procrustes: rmse 0.1648853  max resid 0.3352339 
Run 14 stress 9.305106e-05 
... Procrustes: rmse 0.1364532  max resid 0.2236201 
Run 15 stress 9.089248e-05 
... Procrustes: rmse 0.1557531  max resid 0.2275573 
Run 16 stress 3.884471e-05 
... Procrustes: rmse 0.1223032  max resid 0.1587061 
Run 17 stress 0 
... Procrustes: rmse 0.2005014  max resid 0.2769815 
Run 18 stress 0 
... Procrustes: rmse 0.1390127  max resid 0.1903621 
Run 19 stress 0.2269848 
Run 20 stress 0 
... Procrustes: rmse 0.1159614  max resid 0.1483723 
Run 21 stress 0 
... Procrustes: rmse 0.1153129  max resid 0.2018715 
Run 22 stress 0.0002311025 
... Procrustes: rmse 0.1195525  max resid 0.192406 
Run 23 stress 0.2269842 
Run 24 stress 0 
... Procrustes: rmse 0.1199807  max resid 0.230077 
Run 25 stress 0 
... Procrustes: rmse 0.08480633  max resid 0.1396733 
Run 26 stress 0.2672326 
Run 27 stress 9.693395e-05 
... Procrustes: rmse 0.1477368  max resid 0.1747972 
Run 28 stress 0 
... Procrustes: rmse 0.1298133  max resid 0.1910607 
Run 29 stress 9.842799e-05 
... Procrustes: rmse 0.1501976  max resid 0.240227 
Run 30 stress 6.974657e-05 
... Procrustes: rmse 0.1566156  max resid 0.2573867 
Run 31 stress 9.598797e-05 
... Procrustes: rmse 0.1379217  max resid 0.2111452 
Run 32 stress 0.1470313 
Run 33 stress 0.1470313 
Run 34 stress 0 
... Procrustes: rmse 0.156685  max resid 0.2533842 
Run 35 stress 6.562241e-05 
... Procrustes: rmse 0.1469278  max resid 0.2496937 
Run 36 stress 7.219999e-05 
... Procrustes: rmse 0.1355018  max resid 0.207459 
Run 37 stress 3.258315e-05 
... Procrustes: rmse 0.1384994  max resid 0.2127513 
Run 38 stress 1.278042e-05 
... Procrustes: rmse 0.1218566  max resid 0.1639386 
Run 39 stress 0.2280378 
Run 40 stress 8.471215e-05 
... Procrustes: rmse 0.1198378  max resid 0.1903936 
Run 41 stress 0.2761346 
Run 42 stress 0 
... Procrustes: rmse 0.09595647  max resid 0.1242599 
Run 43 stress 0 
... Procrustes: rmse 0.1387718  max resid 0.2385281 
Run 44 stress 0 
... Procrustes: rmse 0.1483169  max resid 0.2262966 
Run 45 stress 3.098039e-05 
... Procrustes: rmse 0.1092554  max resid 0.1948524 
Run 46 stress 0 
... Procrustes: rmse 0.06070262  max resid 0.08421746 
Run 47 stress 0.2181459 
Run 48 stress 7.805801e-05 
... Procrustes: rmse 0.07728058  max resid 0.1204784 
Run 49 stress 0 
... Procrustes: rmse 0.0237783  max resid 0.03514742 
Run 50 stress 3.37506e-05 
... Procrustes: rmse 0.1498576  max resid 0.2484866 
*** No convergence -- monoMDS stopping criteria:
     1: no. of iterations >= maxit
    37: stress < smin
    11: stress ratio > sratmax
     1: scale factor of the gradient < sfgrmin
stress is (nearly) zero: you may have insufficient data

[[1]]
[[1]][[1]]
[[1]][[1]]$x
 [1] 0.010276771 0.028006530 0.107695950 0.094996348 0.107372465 0.021527691 0.100707321
 [8] 0.090464075 0.101828851 0.092082292 0.081859348 0.093356332 0.015829221 0.008802222
[15] 0.016902250

[[1]][[1]]$y
 [1] 3.561561e-02 1.400662e-01 2.416203e-01 1.580440e-01 2.416230e-01 1.073651e-01
 [7] 2.251203e-01 1.536915e-01 2.251240e-01 1.578027e-01 1.414274e-01 1.578095e-01
[13] 1.034024e-01 8.594704e-06 1.034010e-01

[[1]][[1]]$yf
 [1] 3.561561e-02 1.400662e-01 2.416217e-01 1.580440e-01 2.416217e-01 1.073651e-01
 [7] 2.251203e-01 1.536915e-01 2.251240e-01 1.578027e-01 1.414274e-01 1.578095e-01
[13] 1.034017e-01 8.594704e-06 1.034017e-01


[[1]][[2]]


[[2]]
[[2]][[1]]
[[2]][[1]]$x
 [1] 0.009204274 0.012510909 0.145301457 0.140910131 0.131301795 0.013939975 0.148432054
 [8] 0.146012469 0.135231175 0.151513032 0.147485051 0.136565349 0.012108382 0.028509969
[15] 0.019328989

[[2]][[1]]$y
 [1] 0.01297275 0.02151786 0.28494911 0.27773623 0.25740454 0.02455355 0.29474942 0.28807366
 [9] 0.26850482 0.30047462 0.29227485 0.27027084 0.02005695 0.05415278 0.03483280

[[2]][[1]]$yf
 [1] 0.01297275 0.02151786 0.28494911 0.27773623 0.25740454 0.02455355 0.29474942 0.28807366
 [9] 0.26850482 0.30047462 0.29227485 0.27027084 0.02005695 0.05415278 0.03483280


[[2]][[2]]


[[3]]
[[3]][[1]]
[[3]][[1]]$x
 [1] 0.014031405 0.016757193 0.157854448 0.152590813 0.174071046 0.011473208 0.166926445
 [8] 0.161662441 0.182798589 0.168654974 0.163319190 0.188210584 0.009348346 0.023415623
[15] 0.029340380

[[3]][[1]]$y
 [1] 0.03165700 0.04362705 0.30927524 0.29868014 0.34304689 0.02477087 0.34055452 0.32990048
 [9] 0.37469035 0.34236923 0.33147682 0.37933891 0.01125719 0.05458582 0.06401029

[[3]][[1]]$yf
 [1] 0.03165700 0.04362705 0.30927524 0.29868014 0.34304689 0.02477087 0.34055452 0.32990048
 [9] 0.37469035 0.34236923 0.33147682 0.37933891 0.01125719 0.05458582 0.06401029


[[3]][[2]]


[[4]]
[[4]][[1]]
[[4]][[1]]$x
 [1] 0.01914216 0.21726900 0.23455085 0.21518440 0.01491085 0.20553890 0.22343359 0.20400739
 [9] 0.01923528 0.05234390 0.01582745 0.21060733 0.04196642 0.22578779 0.20782168

[[4]][[1]]$y
 [1] 0.09545722 0.44584428 0.57292705 0.43852141 0.05098696 0.39406134 0.48595284 0.37572478
 [9] 0.09908254 0.28732052 0.06096461 0.40106049 0.23160967 0.54643323 0.39771852

[[4]][[1]]$yf
 [1] 0.09545722 0.44584428 0.57292705 0.43852141 0.05098696 0.39406134 0.48595284 0.37572478
 [9] 0.09908254 0.28732052 0.06096461 0.40106049 0.23160967 0.54643323 0.39771852


[[4]][[2]]

Filler 2

# analyze sample F2_25
lapply(locs, bray_nmds_mock_feed, sodm_filtered_df = mock_feed_sodm_asvs_removed_dataframe, site = "F2_25")
'csv_outputs/bray_dissimilar/mockfeeds' already exists'nperm' >= set of all permutations: complete enumeration.
Set of permutations < 'minperm'. Generating entire set.
Run 0 stress 0 
Run 1 stress 0 
... Procrustes: rmse 0.1223407  max resid 0.2065314 
Run 2 stress 0.2269841 
Run 3 stress 3.808975e-05 
... Procrustes: rmse 0.03470198  max resid 0.05781481 
Run 4 stress 3.962713e-05 
... Procrustes: rmse 0.1259084  max resid 0.1986445 
Run 5 stress 0.2673072 
Run 6 stress 0.2673072 
Run 7 stress 2.205653e-05 
... Procrustes: rmse 0.04972731  max resid 0.08872897 
Run 8 stress 0.2181459 
Run 9 stress 0.2280378 
Run 10 stress 0.2280378 
Run 11 stress 0 
... Procrustes: rmse 0.06448306  max resid 0.1136125 
Run 12 stress 0.2181459 
Run 13 stress 9.985475e-05 
... Procrustes: rmse 0.0517174  max resid 0.08527064 
Run 14 stress 9.899937e-05 
... Procrustes: rmse 0.1113123  max resid 0.2122332 
Run 15 stress 0.2181459 
Run 16 stress 9.795406e-05 
... Procrustes: rmse 0.08753915  max resid 0.1569129 
Run 17 stress 6.791436e-05 
... Procrustes: rmse 0.08009044  max resid 0.1546942 
Run 18 stress 9.01363e-05 
... Procrustes: rmse 0.1734251  max resid 0.2695782 
Run 19 stress 9.70686e-05 
... Procrustes: rmse 0.06170932  max resid 0.09265697 
Run 20 stress 0 
... Procrustes: rmse 0.1063635  max resid 0.1803731 
Run 21 stress 0.2761345 
Run 22 stress 0.2280378 
Run 23 stress 0.2269842 
Run 24 stress 1.753162e-06 
... Procrustes: rmse 0.1362969  max resid 0.2664801 
Run 25 stress 9.648186e-05 
... Procrustes: rmse 0.17437  max resid 0.2406629 
Run 26 stress 0.2269842 
Run 27 stress 0 
... Procrustes: rmse 0.07956493  max resid 0.1535682 
Run 28 stress 0.1557467 
Run 29 stress 0.2181459 
Run 30 stress 0.2761351 
Run 31 stress 0 
... Procrustes: rmse 0.09839422  max resid 0.1634292 
Run 32 stress 1.586183e-05 
... Procrustes: rmse 0.09377439  max resid 0.1662404 
Run 33 stress 0.2280378 
Run 34 stress 0 
... Procrustes: rmse 0.09625735  max resid 0.1736505 
Run 35 stress 0 
... Procrustes: rmse 0.115005  max resid 0.2255002 
Run 36 stress 0.2181459 
Run 37 stress 1.222857e-05 
... Procrustes: rmse 0.1341828  max resid 0.2640306 
Run 38 stress 0.2181459 
Run 39 stress 0 
... Procrustes: rmse 0.1255493  max resid 0.2193809 
Run 40 stress 0.1557467 
Run 41 stress 4.061211e-05 
... Procrustes: rmse 0.1479707  max resid 0.2413699 
Run 42 stress 0.1557467 
Run 43 stress 0 
... Procrustes: rmse 0.1343411  max resid 0.1873171 
Run 44 stress 0 
... Procrustes: rmse 0.1136744  max resid 0.1608809 
Run 45 stress 9.407156e-05 
... Procrustes: rmse 0.1388031  max resid 0.2574358 
Run 46 stress 0.1557467 
Run 47 stress 9.050593e-05 
... Procrustes: rmse 0.08127762  max resid 0.1039046 
Run 48 stress 0.2181459 
Run 49 stress 2.867819e-06 
... Procrustes: rmse 0.08714716  max resid 0.1390009 
Run 50 stress 0 
... Procrustes: rmse 0.1826178  max resid 0.2214629 
*** No convergence -- monoMDS stopping criteria:
    28: stress < smin
    11: stress ratio > sratmax
    11: scale factor of the gradient < sfgrmin
stress is (nearly) zero: you may have insufficient data
Run 0 stress 9.985172e-05 
Run 1 stress 9.675443e-05 
... New best solution
... Procrustes: rmse 0.1121075  max resid 0.16909 
Run 2 stress 0.2672326 
Run 3 stress 5.260601e-05 
... New best solution
... Procrustes: rmse 0.1873748  max resid 0.3449788 
Run 4 stress 0.2181459 
Run 5 stress 8.672378e-05 
... Procrustes: rmse 0.1560671  max resid 0.3048849 
Run 6 stress 0.0005296485 
... Procrustes: rmse 0.1125914  max resid 0.1893854 
Run 7 stress 9.652097e-05 
... Procrustes: rmse 0.07691796  max resid 0.1103629 
Run 8 stress 0.1967694 
Run 9 stress 9.317782e-05 
... Procrustes: rmse 0.1476974  max resid 0.239694 
Run 10 stress 0.000380964 
... Procrustes: rmse 0.1222537  max resid 0.2026794 
Run 11 stress 9.856839e-05 
... Procrustes: rmse 0.1873439  max resid 0.3614229 
Run 12 stress 0.1967694 
Run 13 stress 8.78091e-05 
... Procrustes: rmse 0.1146169  max resid 0.1894954 
Run 14 stress 9.772237e-05 
... Procrustes: rmse 0.1873746  max resid 0.3614209 
Run 15 stress 0.1967694 
Run 16 stress 8.102647e-05 
... Procrustes: rmse 0.02544929  max resid 0.04248186 
Run 17 stress 0.0002723167 
... Procrustes: rmse 0.07291899  max resid 0.1215051 
Run 18 stress 6.687593e-05 
... Procrustes: rmse 0.1024989  max resid 0.1828397 
Run 19 stress 0.0003314391 
... Procrustes: rmse 0.06026818  max resid 0.08163546 
Run 20 stress 0.0008100836 
Run 21 stress 0.2761354 
Run 22 stress 9.327674e-05 
... Procrustes: rmse 0.1467346  max resid 0.2297215 
Run 23 stress 9.58317e-05 
... Procrustes: rmse 0.1873755  max resid 0.3614206 
Run 24 stress 9.644516e-05 
... Procrustes: rmse 0.1873504  max resid 0.3614331 
Run 25 stress 5.47417e-05 
... Procrustes: rmse 0.1528847  max resid 0.2991829 
Run 26 stress 9.823018e-05 
... Procrustes: rmse 0.187374  max resid 0.3614191 
Run 27 stress 9.355997e-05 
... Procrustes: rmse 0.1060145  max resid 0.135654 
Run 28 stress 0.1557467 
Run 29 stress 9.962881e-05 
... Procrustes: rmse 0.1742841  max resid 0.2752743 
Run 30 stress 0.2761355 
Run 31 stress 8.863165e-05 
... Procrustes: rmse 0.1000191  max resid 0.1429708 
Run 32 stress 0 
... New best solution
... Procrustes: rmse 0.03823748  max resid 0.04827639 
Run 33 stress 9.071665e-05 
... Procrustes: rmse 0.143425  max resid 0.2246148 
Run 34 stress 9.690772e-05 
... Procrustes: rmse 0.1444007  max resid 0.2397992 
Run 35 stress 0.0004818294 
... Procrustes: rmse 0.1049189  max resid 0.1677734 
Run 36 stress 0.1967694 
Run 37 stress 0 
... Procrustes: rmse 0.07100411  max resid 0.1226793 
Run 38 stress 8.649133e-05 
... Procrustes: rmse 0.1750531  max resid 0.2757394 
Run 39 stress 7.138159e-05 
... Procrustes: rmse 0.05292396  max resid 0.09925639 
Run 40 stress 0.1557467 
Run 41 stress 9.669527e-05 
... Procrustes: rmse 0.2071734  max resid 0.3785128 
Run 42 stress 0.1557467 
Run 43 stress 9.815866e-05 
... Procrustes: rmse 0.08782676  max resid 0.1677413 
Run 44 stress 9.674277e-05 
... Procrustes: rmse 0.2071389  max resid 0.3783266 
Run 45 stress 8.906234e-05 
... Procrustes: rmse 0.1122843  max resid 0.182787 
Run 46 stress 0.1557467 
Run 47 stress 8.844247e-05 
... Procrustes: rmse 0.06604213  max resid 0.09233335 
Run 48 stress 8.753266e-05 
... Procrustes: rmse 0.1351628  max resid 0.2157915 
Run 49 stress 9.186879e-05 
... Procrustes: rmse 0.2071415  max resid 0.3783281 
Run 50 stress 8.507341e-05 
... Procrustes: rmse 0.04108457  max resid 0.06994378 
*** No convergence -- monoMDS stopping criteria:
     6: no. of iterations >= maxit
    32: stress < smin
     6: stress ratio > sratmax
     6: scale factor of the gradient < sfgrmin

'csv_outputs/bray_dissimilar/mockfeeds' already exists'nperm' >= set of all permutations: complete enumeration.
Set of permutations < 'minperm'. Generating entire set.
Run 0 stress 0 
Run 1 stress 9.27389e-05 
... Procrustes: rmse 0.1521255  max resid 0.229653 
Run 2 stress 8.678388e-05 
... Procrustes: rmse 0.1457964  max resid 0.2075432 
Run 3 stress 9.994686e-05 
... Procrustes: rmse 0.1852294  max resid 0.2419772 
Run 4 stress 9.199759e-05 
... Procrustes: rmse 0.1373251  max resid 0.2063759 
Run 5 stress 9.410999e-05 
... Procrustes: rmse 0.1602437  max resid 0.2493081 
Run 6 stress 8.60815e-05 
... Procrustes: rmse 0.08846057  max resid 0.115434 
Run 7 stress 0 
... Procrustes: rmse 0.08295965  max resid 0.1061013 
Run 8 stress 9.745948e-05 
... Procrustes: rmse 0.136724  max resid 0.1960041 
Run 9 stress 8.348885e-05 
... Procrustes: rmse 0.05872036  max resid 0.0925466 
Run 10 stress 9.957964e-05 
... Procrustes: rmse 0.04630629  max resid 0.08244466 
Run 11 stress 0 
... Procrustes: rmse 0.1479404  max resid 0.2197014 
Run 12 stress 8.530713e-05 
... Procrustes: rmse 0.04799295  max resid 0.08505366 
Run 13 stress 3.636391e-05 
... Procrustes: rmse 0.1374507  max resid 0.2167818 
Run 14 stress 0 
... Procrustes: rmse 0.1631078  max resid 0.2339443 
Run 15 stress 0.2181459 
Run 16 stress 9.822635e-05 
... Procrustes: rmse 0.1106336  max resid 0.2016868 
Run 17 stress 7.288696e-05 
... Procrustes: rmse 0.1673717  max resid 0.3042097 
Run 18 stress 0.2280378 
Run 19 stress 9.838413e-05 
... Procrustes: rmse 0.1275469  max resid 0.1980726 
Run 20 stress 9.786091e-05 
... Procrustes: rmse 0.1871905  max resid 0.2572692 
Run 21 stress 3.048397e-05 
... Procrustes: rmse 0.1030804  max resid 0.1607529 
Run 22 stress 7.114444e-05 
... Procrustes: rmse 0.06017737  max resid 0.09396983 
Run 23 stress 8.875821e-05 
... Procrustes: rmse 0.124411  max resid 0.1675822 
Run 24 stress 0 
... Procrustes: rmse 0.1461035  max resid 0.2201612 
Run 25 stress 0.2181459 
Run 26 stress 0 
... Procrustes: rmse 0.1679669  max resid 0.2317372 
Run 27 stress 0.2761349 
Run 28 stress 0 
... Procrustes: rmse 0.1514277  max resid 0.2227922 
Run 29 stress 0 
... Procrustes: rmse 0.1564645  max resid 0.2247786 
Run 30 stress 0 
... Procrustes: rmse 0.1509248  max resid 0.2735906 
Run 31 stress 7.888498e-05 
... Procrustes: rmse 0.1511732  max resid 0.2622046 
Run 32 stress 0 
... Procrustes: rmse 0.1281077  max resid 0.2386671 
Run 33 stress 8.469696e-05 
... Procrustes: rmse 0.05575747  max resid 0.08619757 
Run 34 stress 8.380588e-05 
... Procrustes: rmse 0.1491894  max resid 0.2197302 
Run 35 stress 9.966382e-05 
... Procrustes: rmse 0.1693455  max resid 0.3146919 
Run 36 stress 9.767769e-05 
... Procrustes: rmse 0.1580556  max resid 0.2702835 
Run 37 stress 9.754226e-05 
... Procrustes: rmse 0.1790055  max resid 0.2677196 
Run 38 stress 0 
... Procrustes: rmse 0.128145  max resid 0.1878178 
Run 39 stress 9.713453e-05 
... Procrustes: rmse 0.184508  max resid 0.2408183 
Run 40 stress 9.174066e-05 
... Procrustes: rmse 0.2033799  max resid 0.3677587 
Run 41 stress 9.740008e-05 
... Procrustes: rmse 0.1122958  max resid 0.1478804 
Run 42 stress 7.044335e-05 
... Procrustes: rmse 0.116211  max resid 0.1389489 
Run 43 stress 7.728447e-05 
... Procrustes: rmse 0.184387  max resid 0.2490613 
Run 44 stress 0.2269842 
Run 45 stress 9.872794e-05 
... Procrustes: rmse 0.1031123  max resid 0.1571142 
Run 46 stress 9.134802e-05 
... Procrustes: rmse 0.1772459  max resid 0.2465256 
Run 47 stress 0.2143661 
Run 48 stress 4.295714e-05 
... Procrustes: rmse 0.04738141  max resid 0.0841658 
Run 49 stress 8.764813e-05 
... Procrustes: rmse 0.08365967  max resid 0.1113174 
Run 50 stress 0.2269841 
*** No convergence -- monoMDS stopping criteria:
    43: stress < smin
     4: stress ratio > sratmax
     3: scale factor of the gradient < sfgrmin
stress is (nearly) zero: you may have insufficient data

'csv_outputs/bray_dissimilar/mockfeeds' already exists'nperm' >= set of all permutations: complete enumeration.
Set of permutations < 'minperm'. Generating entire set.
Run 0 stress 0 
Run 1 stress 3.044087e-06 
... Procrustes: rmse 0.06945111  max resid 0.1122452 
Run 2 stress 0.09533513 
Run 3 stress 6.537764e-05 
... Procrustes: rmse 0.1213111  max resid 0.1569751 
Run 4 stress 0.1259703 
Run 5 stress 0 
... Procrustes: rmse 0.05565396  max resid 0.09658757 
Run 6 stress 0.09533513 
Run 7 stress 0 
... Procrustes: rmse 0.09781367  max resid 0.1349073 
Run 8 stress 0 
... Procrustes: rmse 0.03404197  max resid 0.05373876 
Run 9 stress 0 
... Procrustes: rmse 0.07455857  max resid 0.1109817 
Run 10 stress 9.185812e-10 
... Procrustes: rmse 0.06654021  max resid 0.1076203 
Run 11 stress 6.384493e-05 
... Procrustes: rmse 0.05514556  max resid 0.08763858 
Run 12 stress 8.005973e-05 
... Procrustes: rmse 0.1231277  max resid 0.1965762 
Run 13 stress 6.982077e-05 
... Procrustes: rmse 0.02066864  max resid 0.02752758 
Run 14 stress 0 
... Procrustes: rmse 0.05616963  max resid 0.09282198 
Run 15 stress 5.550769e-05 
... Procrustes: rmse 0.06922159  max resid 0.1064621 
Run 16 stress 7.00079e-05 
... Procrustes: rmse 0.06424896  max resid 0.09448099 
Run 17 stress 0 
... Procrustes: rmse 0.05627784  max resid 0.08437025 
Run 18 stress 8.530485e-05 
... Procrustes: rmse 0.07086376  max resid 0.1132835 
Run 19 stress 0 
... Procrustes: rmse 0.05859341  max resid 0.08067741 
Run 20 stress 0 
... Procrustes: rmse 0.0406491  max resid 0.0564945 
Run 21 stress 0 
... Procrustes: rmse 0.06466189  max resid 0.08488737 
Run 22 stress 2.681044e-05 
... Procrustes: rmse 0.1207179  max resid 0.1820715 
Run 23 stress 0 
... Procrustes: rmse 0.1203763  max resid 0.1591241 
Run 24 stress 0.125969 
Run 25 stress 0 
... Procrustes: rmse 0.05682729  max resid 0.08649165 
Run 26 stress 6.470316e-08 
... Procrustes: rmse 0.06771459  max resid 0.124488 
Run 27 stress 6.32051e-05 
... Procrustes: rmse 0.06896642  max resid 0.1094446 
Run 28 stress 0 
... Procrustes: rmse 0.07119419  max resid 0.1361896 
Run 29 stress 3.063346e-10 
... Procrustes: rmse 0.06904309  max resid 0.11099 
Run 30 stress 0.09533513 
Run 31 stress 0.125969 
Run 32 stress 0.09533513 
Run 33 stress 0 
... Procrustes: rmse 0.06273515  max resid 0.09798401 
Run 34 stress 9.571309e-05 
... Procrustes: rmse 0.06157891  max resid 0.09631296 
Run 35 stress 0.125969 
Run 36 stress 0.09533513 
Run 37 stress 0 
... Procrustes: rmse 0.02611826  max resid 0.03955381 
Run 38 stress 5.394408e-05 
... Procrustes: rmse 0.07123217  max resid 0.1140157 
Run 39 stress 6.281097e-06 
... Procrustes: rmse 0.08023516  max resid 0.1538063 
Run 40 stress 2.118811e-09 
... Procrustes: rmse 0.07042497  max resid 0.1127274 
Run 41 stress 0.09533513 
Run 42 stress 0 
... Procrustes: rmse 0.08976737  max resid 0.1146594 
Run 43 stress 0 
... Procrustes: rmse 0.04177211  max resid 0.06964027 
Run 44 stress 0.2761348 
Run 45 stress 8.809518e-05 
... Procrustes: rmse 0.1260357  max resid 0.2157152 
Run 46 stress 0 
... Procrustes: rmse 0.0753679  max resid 0.1036992 
Run 47 stress 0 
... Procrustes: rmse 0.02392609  max resid 0.04095896 
Run 48 stress 0 
... Procrustes: rmse 0.1252648  max resid 0.2231107 
Run 49 stress 0.09533513 
Run 50 stress 0.1010567 
*** No convergence -- monoMDS stopping criteria:
    37: stress < smin
     6: stress ratio > sratmax
     7: scale factor of the gradient < sfgrmin
stress is (nearly) zero: you may have insufficient data

[[1]]
[[1]][[1]]
[[1]][[1]]$x
 [1] 0.006254553 0.029116235 0.209788654 0.280934147 0.281559959 0.030475264 0.208871595
 [8] 0.278804603 0.279733500 0.207286778 0.266285549 0.269911406 0.150834932 0.146068287
[15] 0.021336136

[[1]][[1]]$y
 [1] 0.003958143 0.038696260 0.409424620 0.546925832 0.547290722 0.040801233 0.406401320
 [8] 0.545720228 0.545965978 0.404274865 0.521620989 0.522948826 0.295238280 0.282769190
[15] 0.017362503

[[1]][[1]]$yf
 [1] 0.003958143 0.038696260 0.409424620 0.546925832 0.547290722 0.040801233 0.406401320
 [8] 0.545720228 0.545965978 0.404274865 0.521620989 0.522948826 0.295238280 0.282769190
[15] 0.017362503


[[1]][[2]]


[[2]]
[[2]][[1]]
[[2]][[1]]$x
 [1] 0.007527942 0.028883500 0.124233078 0.127565146 0.128719857 0.029900682 0.126736958
 [8] 0.126156096 0.127319350 0.133097868 0.149405482 0.149215845 0.032682434 0.039362729
[15] 0.012821449

[[2]][[1]]$y
 [1] 0.04051713 0.07833811 0.23820451 0.26675690 0.27491556 0.07863105 0.24357795 0.24287441
 [9] 0.24585736 0.31530588 0.31890361 0.31780077 0.18506301 0.22600040 0.04387713

[[2]][[1]]$yf
 [1] 0.04051713 0.07833811 0.23820451 0.26675690 0.27491556 0.07863105 0.24357795 0.24287441
 [9] 0.24585736 0.31530588 0.31890361 0.31780077 0.18506301 0.22600040 0.04387713


[[2]][[2]]


[[3]]
[[3]][[1]]
[[3]][[1]]$x
 [1] 0.22744092 0.23312397 0.22601228 0.01609754 0.01069745 0.02090434 0.03128485 0.21749839
 [9] 0.22983959 0.05060696 0.22317568 0.23528745 0.21620894 0.22796633 0.02092702

[[3]][[1]]$y
 [1] 0.449420251 0.462354040 0.447578162 0.027186246 0.007874912 0.029394970 0.066387340
 [8] 0.422278681 0.456667117 0.094711652 0.435167874 0.469765678 0.420989785 0.454295726
[15] 0.034689145

[[3]][[1]]$yf
 [1] 0.449420251 0.462354040 0.447578162 0.027186246 0.007874912 0.029394970 0.066387340
 [8] 0.422278681 0.456667117 0.094711652 0.435167874 0.469765678 0.420989785 0.454295726
[15] 0.034689145


[[3]][[2]]


[[4]]
[[4]][[1]]
[[4]][[1]]$x
 [1] 0.22155767 0.15323750 0.28820302 0.03427779 0.16545378 0.09748013 0.27884522 0.21610143
 [9] 0.22830578 0.22614810 0.14960398 0.16283834 0.30771502 0.19371545 0.19243508

[[4]][[1]]$y
 [1] 0.39630973 0.23733902 0.54180934 0.02265569 0.26045042 0.18410006 0.51266545 0.38885277
 [9] 0.43211928 0.41636644 0.23709329 0.25689307 0.55759036 0.29855452 0.28003217

[[4]][[1]]$yf
 [1] 0.39630973 0.23733902 0.54180934 0.02265569 0.26045042 0.18410006 0.51266545 0.38885277
 [9] 0.43211928 0.41636644 0.23709329 0.25689307 0.55759036 0.29855452 0.28003217


[[4]][[2]]

# analyze sample F2_0
lapply(locs, bray_nmds_mock_feed, sodm_filtered_df = mock_feed_sodm_asvs_removed_dataframe, site = "F2_0")
'csv_outputs/bray_dissimilar/mockfeeds' already exists'nperm' >= set of all permutations: complete enumeration.
Set of permutations < 'minperm'. Generating entire set.
Run 0 stress 7.188377e-05 
Run 1 stress 0.2761351 
Run 2 stress 0.2269841 
Run 3 stress 8.101582e-05 
... Procrustes: rmse 0.1378511  max resid 0.2526561 
Run 4 stress 0 
... New best solution
... Procrustes: rmse 0.1525377  max resid 0.226433 
Run 5 stress 0.2029041 
Run 6 stress 0.2269841 
Run 7 stress 0 
... Procrustes: rmse 0.08668495  max resid 0.1330141 
Run 8 stress 2.207403e-05 
... Procrustes: rmse 0.1064627  max resid 0.1864247 
Run 9 stress 0 
... Procrustes: rmse 0.1337557  max resid 0.2051906 
Run 10 stress 1.753599e-06 
... Procrustes: rmse 0.1385379  max resid 0.237886 
Run 11 stress 0.2673072 
Run 12 stress 0 
... Procrustes: rmse 0.02836019  max resid 0.04187944 
Run 13 stress 8.025176e-05 
... Procrustes: rmse 0.0726192  max resid 0.09454725 
Run 14 stress 0 
... Procrustes: rmse 0.1502222  max resid 0.2265897 
Run 15 stress 0 
... Procrustes: rmse 0.1126678  max resid 0.1710298 
Run 16 stress 0 
... Procrustes: rmse 0.06281334  max resid 0.09094605 
Run 17 stress 0 
... Procrustes: rmse 0.1615955  max resid 0.2285288 
Run 18 stress 0 
... Procrustes: rmse 0.1450466  max resid 0.2852576 
Run 19 stress 0 
... Procrustes: rmse 0.04245243  max resid 0.06966204 
Run 20 stress 0 
... Procrustes: rmse 0.1325092  max resid 0.248607 
Run 21 stress 0 
... Procrustes: rmse 0.08177226  max resid 0.100589 
Run 22 stress 0 
... Procrustes: rmse 0.02510671  max resid 0.04018133 
Run 23 stress 0 
... Procrustes: rmse 0.1203113  max resid 0.1599242 
Run 24 stress 0 
... Procrustes: rmse 0.0500644  max resid 0.07866878 
Run 25 stress 0 
... Procrustes: rmse 0.06084285  max resid 0.1117558 
Run 26 stress 0 
... Procrustes: rmse 0.09056388  max resid 0.09650411 
Run 27 stress 0.2181459 
Run 28 stress 0 
... Procrustes: rmse 0.02738887  max resid 0.04845312 
Run 29 stress 0 
... Procrustes: rmse 0.07434677  max resid 0.1257995 
Run 30 stress 0 
... Procrustes: rmse 0.08481603  max resid 0.109632 
Run 31 stress 0 
... Procrustes: rmse 0.1299555  max resid 0.2348551 
Run 32 stress 0 
... Procrustes: rmse 0.1188175  max resid 0.1970214 
Run 33 stress 0 
... Procrustes: rmse 0.1458604  max resid 0.2258245 
Run 34 stress 0 
... Procrustes: rmse 0.08512322  max resid 0.1248643 
Run 35 stress 9.093154e-05 
... Procrustes: rmse 0.1407966  max resid 0.2496436 
Run 36 stress 0.2029041 
Run 37 stress 0 
... Procrustes: rmse 0.1180612  max resid 0.1947868 
Run 38 stress 0.2672326 
Run 39 stress 0 
... Procrustes: rmse 0.08427885  max resid 0.1212251 
Run 40 stress 0 
... Procrustes: rmse 0.1243431  max resid 0.2343176 
Run 41 stress 0 
... Procrustes: rmse 0.06531926  max resid 0.1157826 
Run 42 stress 0 
... Procrustes: rmse 0.1126321  max resid 0.1569682 
Run 43 stress 0 
... Procrustes: rmse 0.07263194  max resid 0.1225922 
Run 44 stress 9.321316e-05 
... Procrustes: rmse 0.04294484  max resid 0.06979101 
Run 45 stress 0 
... Procrustes: rmse 0.05850514  max resid 0.09685507 
Run 46 stress 0 
... Procrustes: rmse 0.09218628  max resid 0.1481359 
Run 47 stress 5.204586e-05 
... Procrustes: rmse 0.1492392  max resid 0.2331048 
Run 48 stress 0.2269841 
Run 49 stress 0.2181459 
Run 50 stress 0 
... Procrustes: rmse 0.1642012  max resid 0.2604613 
*** No convergence -- monoMDS stopping criteria:
    40: stress < smin
     7: stress ratio > sratmax
     3: scale factor of the gradient < sfgrmin
stress is (nearly) zero: you may have insufficient data
Run 0 stress 7.921199e-05 
Run 1 stress 2.075768e-11 
... New best solution
... Procrustes: rmse 0.1533861  max resid 0.2486492 
Run 2 stress 0.1970957 
Run 3 stress 0 
... New best solution
... Procrustes: rmse 0.1416719  max resid 0.1714828 
Run 4 stress 0 
... Procrustes: rmse 0.1578028  max resid 0.2248607 
Run 5 stress 0 
... Procrustes: rmse 0.1204965  max resid 0.2121441 
Run 6 stress 0.2269841 
Run 7 stress 0 
... Procrustes: rmse 0.1578575  max resid 0.2702088 
Run 8 stress 9.602541e-05 
... Procrustes: rmse 0.1293948  max resid 0.2358058 
Run 9 stress 3.310182e-05 
... Procrustes: rmse 0.1481482  max resid 0.2903267 
Run 10 stress 0.2181459 
Run 11 stress 0.2181459 
Run 12 stress 0 
... Procrustes: rmse 0.1646221  max resid 0.2684588 
Run 13 stress 0 
... Procrustes: rmse 0.1392139  max resid 0.1637873 
Run 14 stress 0 
... Procrustes: rmse 0.1121501  max resid 0.2043825 
Run 15 stress 0 
... Procrustes: rmse 0.1560801  max resid 0.1875962 
Run 16 stress 0 
... Procrustes: rmse 0.1463231  max resid 0.2808581 
Run 17 stress 9.773829e-05 
... Procrustes: rmse 0.1419352  max resid 0.2911118 
Run 18 stress 0 
... Procrustes: rmse 0.1905914  max resid 0.3381266 
Run 19 stress 0 
... Procrustes: rmse 0.2066693  max resid 0.3495548 
Run 20 stress 9.807275e-05 
... Procrustes: rmse 0.09424447  max resid 0.1587148 
Run 21 stress 0.1967694 
Run 22 stress 0 
... Procrustes: rmse 0.1510066  max resid 0.2465763 
Run 23 stress 4.133679e-05 
... Procrustes: rmse 0.06409936  max resid 0.0891886 
Run 24 stress 7.563102e-05 
... Procrustes: rmse 0.1462  max resid 0.2622727 
Run 25 stress 0 
... Procrustes: rmse 0.1566686  max resid 0.2474357 
Run 26 stress 1.172297e-05 
... Procrustes: rmse 0.1545732  max resid 0.196343 
Run 27 stress 0 
... Procrustes: rmse 0.08942632  max resid 0.137192 
Run 28 stress 8.807683e-05 
... Procrustes: rmse 0.2048099  max resid 0.2671347 
Run 29 stress 1.080862e-08 
... Procrustes: rmse 0.1402199  max resid 0.2062496 
Run 30 stress 0 
... Procrustes: rmse 0.1223546  max resid 0.172425 
Run 31 stress 9.185906e-05 
... Procrustes: rmse 0.1150748  max resid 0.1763716 
Run 32 stress 0 
... Procrustes: rmse 0.1269937  max resid 0.1694881 
Run 33 stress 0.2181459 
Run 34 stress 0 
... Procrustes: rmse 0.1509814  max resid 0.2046099 
Run 35 stress 0 
... Procrustes: rmse 0.06944273  max resid 0.09392927 
Run 36 stress 0.2761385 
Run 37 stress 0 
... Procrustes: rmse 0.132748  max resid 0.239956 
Run 38 stress 0.2672326 
Run 39 stress 0 
... Procrustes: rmse 0.1441822  max resid 0.2659112 
Run 40 stress 0 
... Procrustes: rmse 0.08825797  max resid 0.168706 
Run 41 stress 0 
... Procrustes: rmse 0.1446988  max resid 0.3042454 
Run 42 stress 0 
... Procrustes: rmse 0.06367835  max resid 0.1116393 
Run 43 stress 0 
... Procrustes: rmse 0.1144281  max resid 0.1867821 
Run 44 stress 5.76876e-06 
... Procrustes: rmse 0.0732613  max resid 0.1032739 
Run 45 stress 0 
... Procrustes: rmse 0.1324367  max resid 0.2025857 
Run 46 stress 0 
... Procrustes: rmse 0.1394626  max resid 0.222258 
Run 47 stress 0 
... Procrustes: rmse 0.1394865  max resid 0.2623241 
Run 48 stress 0.2269841 
Run 49 stress 0 
... Procrustes: rmse 0.07662625  max resid 0.1104388 
Run 50 stress 6.526912e-05 
... Procrustes: rmse 0.1430293  max resid 0.2856894 
*** No convergence -- monoMDS stopping criteria:
    41: stress < smin
     6: stress ratio > sratmax
     3: scale factor of the gradient < sfgrmin

'csv_outputs/bray_dissimilar/mockfeeds' already exists'nperm' >= set of all permutations: complete enumeration.
Set of permutations < 'minperm'. Generating entire set.
Run 0 stress 2.249929e-05 
Run 1 stress 0.2761349 
Run 2 stress 2.289779e-05 
... Procrustes: rmse 0.1866514  max resid 0.2494207 
Run 3 stress 9.333211e-05 
... Procrustes: rmse 0.154691  max resid 0.3092455 
Run 4 stress 0 
... New best solution
... Procrustes: rmse 0.08838499  max resid 0.1462992 
Run 5 stress 2.154406e-05 
... Procrustes: rmse 0.1545686  max resid 0.2452741 
Run 6 stress 9.832436e-05 
... Procrustes: rmse 0.0754475  max resid 0.1522155 
Run 7 stress 9.852451e-05 
... Procrustes: rmse 0.09468275  max resid 0.1475169 
Run 8 stress 8.484662e-05 
... Procrustes: rmse 0.1130575  max resid 0.2311013 
Run 9 stress 0 
... Procrustes: rmse 0.1166551  max resid 0.179319 
Run 10 stress 0.2269842 
Run 11 stress 0.2269842 
Run 12 stress 0 
... Procrustes: rmse 0.1335803  max resid 0.2547946 
Run 13 stress 9.268887e-05 
... Procrustes: rmse 0.1385014  max resid 0.2180462 
Run 14 stress 0 
... Procrustes: rmse 0.07960846  max resid 0.1187512 
Run 15 stress 9.436316e-05 
... Procrustes: rmse 0.1021358  max resid 0.1608005 
Run 16 stress 0 
... Procrustes: rmse 0.0941109  max resid 0.1596651 
Run 17 stress 0 
... Procrustes: rmse 0.1556236  max resid 0.2814113 
Run 18 stress 0 
... Procrustes: rmse 0.07752391  max resid 0.1258718 
Run 19 stress 7.960643e-05 
... Procrustes: rmse 0.1297613  max resid 0.2015067 
Run 20 stress 4.529276e-05 
... Procrustes: rmse 0.1412719  max resid 0.2739843 
Run 21 stress 9.414278e-05 
... Procrustes: rmse 0.1699047  max resid 0.320062 
Run 22 stress 0 
... Procrustes: rmse 0.0969024  max resid 0.1752751 
Run 23 stress 6.63577e-05 
... Procrustes: rmse 0.1262935  max resid 0.254712 
Run 24 stress 9.696424e-05 
... Procrustes: rmse 0.1602765  max resid 0.3000258 
Run 25 stress 0.2269842 
Run 26 stress 0.2673072 
Run 27 stress 0.2181459 
Run 28 stress 0 
... Procrustes: rmse 0.08365868  max resid 0.1325619 
Run 29 stress 0.2761341 
Run 30 stress 0.2181459 
Run 31 stress 0 
... Procrustes: rmse 0.07536874  max resid 0.1042113 
Run 32 stress 0 
... Procrustes: rmse 0.125977  max resid 0.2380113 
Run 33 stress 0 
... Procrustes: rmse 0.09280766  max resid 0.129987 
Run 34 stress 0 
... Procrustes: rmse 0.09076951  max resid 0.1739668 
Run 35 stress 9.515772e-05 
... Procrustes: rmse 0.1120239  max resid 0.1794874 
Run 36 stress 8.828599e-05 
... Procrustes: rmse 0.1514146  max resid 0.2422186 
Run 37 stress 9.262122e-05 
... Procrustes: rmse 0.1188812  max resid 0.1814029 
Run 38 stress 0.2269841 
Run 39 stress 0 
... Procrustes: rmse 0.133943  max resid 0.2603554 
Run 40 stress 0 
... Procrustes: rmse 0.05248697  max resid 0.07462505 
Run 41 stress 9.244271e-05 
... Procrustes: rmse 0.1182056  max resid 0.1728993 
Run 42 stress 8.949273e-05 
... Procrustes: rmse 0.1406998  max resid 0.2721431 
Run 43 stress 9.528495e-05 
... Procrustes: rmse 0.1912779  max resid 0.3565254 
Run 44 stress 9.271712e-05 
... Procrustes: rmse 0.09126982  max resid 0.126712 
Run 45 stress 0.2673072 
Run 46 stress 9.246815e-05 
... Procrustes: rmse 0.09829775  max resid 0.1586411 
Run 47 stress 0 
... Procrustes: rmse 0.117014  max resid 0.1731356 
Run 48 stress 8.059002e-05 
... Procrustes: rmse 0.07977944  max resid 0.1675462 
Run 49 stress 7.023664e-05 
... Procrustes: rmse 0.1024447  max resid 0.1708959 
Run 50 stress 0.00108158 
*** No convergence -- monoMDS stopping criteria:
     1: no. of iterations >= maxit
    39: stress < smin
     7: stress ratio > sratmax
     3: scale factor of the gradient < sfgrmin
stress is (nearly) zero: you may have insufficient data

'csv_outputs/bray_dissimilar/mockfeeds' already exists'nperm' >= set of all permutations: complete enumeration.
Set of permutations < 'minperm'. Generating entire set.
Run 0 stress 0 
Run 1 stress 0.2761361 
Run 2 stress 0.150716 
Run 3 stress 0.1336414 
Run 4 stress 8.382761e-05 
... Procrustes: rmse 0.0568723  max resid 0.09393385 
Run 5 stress 0.150716 
Run 6 stress 0 
... Procrustes: rmse 0.09999198  max resid 0.1378761 
Run 7 stress 0 
... Procrustes: rmse 0.116781  max resid 0.1636341 
Run 8 stress 9.855595e-05 
... Procrustes: rmse 0.1342877  max resid 0.1656941 
Run 9 stress 9.946945e-05 
... Procrustes: rmse 0.08573196  max resid 0.16378 
Run 10 stress 7.003845e-05 
... Procrustes: rmse 0.08585058  max resid 0.1639405 
Run 11 stress 0.1506039 
Run 12 stress 0 
... Procrustes: rmse 0.1260673  max resid 0.1620707 
Run 13 stress 8.562925e-05 
... Procrustes: rmse 0.06288703  max resid 0.1125769 
Run 14 stress 0.1066982 
Run 15 stress 0 
... Procrustes: rmse 0.1123722  max resid 0.1772052 
Run 16 stress 0 
... Procrustes: rmse 0.1229127  max resid 0.1741901 
Run 17 stress 0.1336444 
Run 18 stress 0.1066982 
Run 19 stress 0.1336455 
Run 20 stress 0 
... Procrustes: rmse 0.0865444  max resid 0.1188462 
Run 21 stress 0.1066982 
Run 22 stress 7.487884e-05 
... Procrustes: rmse 0.06640352  max resid 0.1192449 
Run 23 stress 0.1506027 
Run 24 stress 0.150603 
Run 25 stress 0.2673072 
Run 26 stress 0.2269841 
Run 27 stress 0 
... Procrustes: rmse 0.1232387  max resid 0.1502887 
Run 28 stress 0 
... Procrustes: rmse 0.1011606  max resid 0.1449335 
Run 29 stress 0.1506028 
Run 30 stress 0.2761355 
Run 31 stress 0 
... Procrustes: rmse 0.06900626  max resid 0.1135598 
Run 32 stress 9.086962e-05 
... Procrustes: rmse 0.1157697  max resid 0.1649378 
Run 33 stress 0 
... Procrustes: rmse 0.03331736  max resid 0.06808534 
Run 34 stress 2.325576e-05 
... Procrustes: rmse 0.01470123  max resid 0.02841497 
Run 35 stress 8.916882e-05 
... Procrustes: rmse 0.07114589  max resid 0.1251688 
Run 36 stress 0 
... Procrustes: rmse 0.07492711  max resid 0.1221508 
Run 37 stress 0 
... Procrustes: rmse 0.1078112  max resid 0.1395469 
Run 38 stress 0.1506022 
Run 39 stress 0.1336385 
Run 40 stress 0 
... Procrustes: rmse 0.1101607  max resid 0.1556894 
Run 41 stress 0 
... Procrustes: rmse 0.07371134  max resid 0.1049192 
Run 42 stress 9.96391e-05 
... Procrustes: rmse 0.07384028  max resid 0.1409495 
Run 43 stress 9.391698e-05 
... Procrustes: rmse 0.1257046  max resid 0.171469 
Run 44 stress 0 
... Procrustes: rmse 0.04399256  max resid 0.06262103 
Run 45 stress 8.620591e-05 
... Procrustes: rmse 0.08354666  max resid 0.1592804 
Run 46 stress 0 
... Procrustes: rmse 0.1151094  max resid 0.157271 
Run 47 stress 0 
... Procrustes: rmse 0.0875442  max resid 0.1675373 
Run 48 stress 0.1506027 
Run 49 stress 9.098117e-05 
... Procrustes: rmse 0.1327475  max resid 0.1671193 
Run 50 stress 0 
... Procrustes: rmse 0.07512905  max resid 0.1449246 
*** No convergence -- monoMDS stopping criteria:
    31: stress < smin
    18: stress ratio > sratmax
     1: scale factor of the gradient < sfgrmin
stress is (nearly) zero: you may have insufficient data

[[1]]
[[1]][[1]]
[[1]][[1]]$x
 [1] 0.009759950 0.012697374 0.106741779 0.107719610 0.107220948 0.018422623 0.113049520
 [8] 0.114101491 0.113528689 0.100255074 0.101307045 0.100745589 0.002069468 0.003748236
[15] 0.002644918

[[1]][[1]]$y
 [1] 0.10986126 0.11636147 0.20436522 0.22821371 0.21310424 0.12572227 0.25644523 0.28144853
 [9] 0.27513739 0.13342851 0.15796416 0.15542623 0.02509673 0.02862736 0.02573959

[[1]][[1]]$yf
 [1] 0.10986126 0.11636147 0.20436522 0.22821371 0.21310424 0.12572227 0.25644523 0.28144853
 [9] 0.27513739 0.13342851 0.15796416 0.15542623 0.02509673 0.02862736 0.02573959


[[1]][[2]]


[[2]]
[[2]][[1]]
[[2]][[1]]$x
 [1] 0.020268396 0.021856260 0.136126971 0.138332242 0.137020727 0.030853036 0.145359258
 [8] 0.147578134 0.146326074 0.119078536 0.121406474 0.120094958 0.004083416 0.003552271
[15] 0.004815322

[[2]][[1]]$y
 [1] 0.06539700 0.13583689 0.26472821 0.30771041 0.26770604 0.20038657 0.31788916 0.36226874
 [9] 0.31939228 0.20752368 0.23897187 0.21556131 0.04530313 0.01121646 0.04773670

[[2]][[1]]$yf
 [1] 0.06539700 0.13583689 0.26472821 0.30771041 0.26770604 0.20038657 0.31788916 0.36226874
 [9] 0.31939228 0.20752368 0.23897187 0.21556131 0.04530313 0.01121646 0.04773670


[[2]][[2]]


[[3]]
[[3]][[1]]
[[3]][[1]]$x
 [1] 0.014363096 0.017098114 0.103479974 0.105070305 0.102671486 0.015713784 0.102965706
 [8] 0.104496389 0.102109929 0.089372677 0.090903360 0.088539120 0.003548708 0.013536289
[15] 0.012326219

[[3]][[1]]$y
 [1] 0.07401970 0.08605525 0.22486407 0.23245617 0.21451979 0.07998893 0.22273181 0.22595666
 [9] 0.20771160 0.14655891 0.15184406 0.13349611 0.01446419 0.01883708 0.01837334

[[3]][[1]]$yf
 [1] 0.07401970 0.08605525 0.22486407 0.23245617 0.21451979 0.07998893 0.22273181 0.22595666
 [9] 0.20771160 0.14655891 0.15184406 0.13349611 0.01446419 0.01883708 0.01837334


[[3]][[2]]


[[4]]
[[4]][[1]]
[[4]][[1]]$x
 [1] 0.44920819 0.08412974 0.16748595 0.42854620 0.42488322 0.49129790 0.55417671 0.50243832
 [9] 0.47076895 0.14165210 0.46357103 0.46259384 0.39364137 0.39806751 0.09785464

[[4]][[1]]$y
 [1] 0.86126800 0.07032648 0.26368904 0.82129043 0.81034709 0.92533278 1.05716795 0.96744014
 [9] 0.88266625 0.25214365 0.87256632 0.86659841 0.73646971 0.75581155 0.09301924

[[4]][[1]]$yf
 [1] 0.86126800 0.07032648 0.26368904 0.82129043 0.81034709 0.92533278 1.05716795 0.96744014
 [9] 0.88266625 0.25214365 0.87256632 0.86659841 0.73646971 0.75581155 0.09301924


[[4]][[2]]

Mock feed pools

# analyze the mock equal pool samples
lapply(locs, bray_nmds_mock_feed, sodm_filtered_df = mock_feed_sodm_asvs_removed_dataframe, site = "MEP")
'csv_outputs/bray_dissimilar/mockfeeds' already existsExpected 4 pieces. Missing pieces filled with `NA` in 9 rows [1, 2, 3, 4, 5, 6, 7, 8, 9].
Run 0 stress 0.1055467 
Run 1 stress 0.1082629 
Run 2 stress 0.185943 
Run 3 stress 0.1350568 
Run 4 stress 0.1082629 
Run 5 stress 0.1842716 
Run 6 stress 0.145019 
Run 7 stress 0.1450194 
Run 8 stress 0.1540806 
Run 9 stress 0.1055472 
... Procrustes: rmse 0.0005453899  max resid 0.0009278687 
... Similar to previous best
Run 10 stress 0.1350487 
Run 11 stress 0.1082629 
Run 12 stress 0.1450191 
Run 13 stress 0.1055468 
... Procrustes: rmse 8.963047e-05  max resid 0.0001364126 
... Similar to previous best
Run 14 stress 0.2149903 
Run 15 stress 0.1859443 
Run 16 stress 0.137732 
Run 17 stress 0.1540805 
Run 18 stress 0.1082629 
Run 19 stress 0.1082629 
Run 20 stress 0.137732 
*** Solution reached
Run 0 stress 0.1158061 
Run 1 stress 0.169118 
Run 2 stress 0.1964301 
Run 3 stress 0.1646112 
Run 4 stress 0.1691181 
Run 5 stress 0.1158046 
... New best solution
... Procrustes: rmse 0.0009669174  max resid 0.002062334 
... Similar to previous best
Run 6 stress 0.1382198 
Run 7 stress 0.2489173 
Run 8 stress 0.2929585 
Run 9 stress 0.1757775 
Run 10 stress 0.1894733 
Run 11 stress 0.1625856 
Run 12 stress 0.1382199 
Run 13 stress 0.1158048 
... Procrustes: rmse 0.0002544148  max resid 0.0005257369 
... Similar to previous best
Run 14 stress 0.1691182 
Run 15 stress 0.1382243 
Run 16 stress 0.1897223 
Run 17 stress 0.1964301 
Run 18 stress 0.1158048 
... Procrustes: rmse 0.0002111826  max resid 0.0004449285 
... Similar to previous best
Run 19 stress 0.169118 
Run 20 stress 0.1382201 
*** Solution reached

'csv_outputs/bray_dissimilar/mockfeeds' already existsExpected 4 pieces. Missing pieces filled with `NA` in 9 rows [1, 2, 3, 4, 5, 6, 7, 8, 9].
Run 0 stress 0.1266085 
Run 1 stress 0.1250975 
... New best solution
... Procrustes: rmse 0.1116371  max resid 0.1714849 
Run 2 stress 0.1237007 
... New best solution
... Procrustes: rmse 0.1878832  max resid 0.3629085 
Run 3 stress 0.1237007 
... New best solution
... Procrustes: rmse 9.328018e-06  max resid 1.804131e-05 
... Similar to previous best
Run 4 stress 0.1340103 
Run 5 stress 0.1266086 
Run 6 stress 0.142726 
Run 7 stress 0.142726 
Run 8 stress 0.1237007 
... New best solution
... Procrustes: rmse 5.768097e-06  max resid 1.027572e-05 
... Similar to previous best
Run 9 stress 0.1237007 
... Procrustes: rmse 1.872509e-05  max resid 3.664431e-05 
... Similar to previous best
Run 10 stress 0.1250975 
Run 11 stress 0.2546845 
Run 12 stress 0.3017341 
Run 13 stress 0.1340063 
Run 14 stress 0.1427261 
Run 15 stress 0.2439358 
Run 16 stress 0.17619 
Run 17 stress 0.211868 
Run 18 stress 0.1250976 
Run 19 stress 0.142726 
Run 20 stress 0.142726 
*** Solution reached

'csv_outputs/bray_dissimilar/mockfeeds' already existsExpected 4 pieces. Missing pieces filled with `NA` in 9 rows [1, 2, 3, 4, 5, 6, 7, 8, 9].
Run 0 stress 9.252521e-05 
Run 1 stress 9.764809e-05 
... Procrustes: rmse 2.100437e-05  max resid 3.82702e-05 
... Similar to previous best
Run 2 stress 0.002703715 
Run 3 stress 9.36114e-05 
... Procrustes: rmse 3.36271e-06  max resid 4.621912e-06 
... Similar to previous best
Run 4 stress 0.3017343 
Run 5 stress 9.669343e-05 
... Procrustes: rmse 1.858604e-05  max resid 3.408368e-05 
... Similar to previous best
Run 6 stress 0.1089013 
Run 7 stress 0.005645638 
Run 8 stress 8.078914e-05 
... New best solution
... Procrustes: rmse 4.373645e-05  max resid 7.176272e-05 
... Similar to previous best
Run 9 stress 9.631914e-05 
... Procrustes: rmse 5.622295e-05  max resid 9.228164e-05 
... Similar to previous best
Run 10 stress 9.654678e-05 
... Procrustes: rmse 5.534527e-05  max resid 9.380193e-05 
... Similar to previous best
Run 11 stress 9.801693e-05 
... Procrustes: rmse 7.706965e-05  max resid 0.0001305659 
... Similar to previous best
Run 12 stress 9.609074e-05 
... Procrustes: rmse 5.498922e-05  max resid 9.039059e-05 
... Similar to previous best
Run 13 stress 8.184136e-05 
... Procrustes: rmse 1.879096e-05  max resid 3.095525e-05 
... Similar to previous best
Run 14 stress 9.902215e-05 
... Procrustes: rmse 6.492789e-05  max resid 0.0001084927 
... Similar to previous best
Run 15 stress 9.979534e-05 
... Procrustes: rmse 6.527762e-05  max resid 0.0001107576 
... Similar to previous best
Run 16 stress 9.590348e-05 
... Procrustes: rmse 4.904905e-05  max resid 8.040971e-05 
... Similar to previous best
Run 17 stress 9.643764e-05 
... Procrustes: rmse 6.578904e-05  max resid 0.0001117304 
... Similar to previous best
Run 18 stress 9.970145e-05 
... Procrustes: rmse 6.924329e-05  max resid 0.0001305982 
... Similar to previous best
Run 19 stress 0.1089011 
Run 20 stress 9.763823e-05 
... Procrustes: rmse 6.604179e-05  max resid 0.0001269389 
... Similar to previous best
*** Solution reached
stress is (nearly) zero: you may have insufficient data

[[1]]
[[1]][[1]]
[[1]][[1]]$x
 [1] 0.3357518 0.2700306 0.3595434 0.3959025 0.2204576 0.3101452 0.2962518 0.3627042 0.3426059
[10] 0.4577952 0.4882227 0.3241198 0.3621956 0.4440666 0.3942616 0.3017729 0.4115382 0.2685351
[19] 0.3521591 0.3325456 0.3534061 0.4205420 0.3640889 0.3631096 0.3920352 0.4236946 0.3844125
[28] 0.3600025 0.3515579 0.3938477 0.2922536 0.2993083 0.3530073 0.3647150 0.4454963 0.3201164

[[1]][[1]]$y
 [1] 0.23617078 0.03762539 0.34190840 0.37359948 0.01694579 0.20414470 0.24583515 0.29980948
 [9] 0.27107710 0.55632187 0.60388473 0.23595070 0.34105021 0.45112702 0.39758255 0.30475073
[17] 0.34558687 0.04763455 0.18524065 0.23232901 0.31380347 0.29502070 0.35187729 0.25040571
[25] 0.35937602 0.54779261 0.36999401 0.44130328 0.18271943 0.38441925 0.22091932 0.23567211
[33] 0.28303100 0.39018754 0.49904352 0.20926698

[[1]][[1]]$yf
 [1] 0.23119612 0.04262997 0.33489542 0.36447080 0.01694579 0.23119612 0.23119612 0.33489542
 [9] 0.23119612 0.55632187 0.60388473 0.23119612 0.33489542 0.49932105 0.36447080 0.23119612
[17] 0.36447080 0.04262997 0.23119612 0.23119612 0.31380347 0.36447080 0.35187729 0.33489542
[25] 0.36447080 0.49932105 0.36447080 0.33489542 0.23119612 0.36447080 0.22091932 0.23119612
[33] 0.28303100 0.36447080 0.49932105 0.23119612


[[1]][[2]]


[[2]]
[[2]][[1]]
[[2]][[1]]$x
 [1] 0.3001029 0.3617612 0.3231230 0.2837100 0.3312523 0.3308951 0.2797711 0.3789591 0.2477878
[10] 0.2713214 0.2712994 0.2282147 0.2629750 0.2515766 0.2194640 0.2622830 0.3090623 0.3005126
[19] 0.2954255 0.2879893 0.2816027 0.2818472 0.2836117 0.3015214 0.2648673 0.3206234 0.2990247
[28] 0.2569708 0.2657031 0.3295128 0.2778473 0.2731560 0.2737862 0.3047030 0.2708267 0.2985946

[[2]][[1]]$y
 [1] 0.24312184 0.31656928 0.21939429 0.17623836 0.31805430 0.29714638 0.15851120 0.37878522
 [9] 0.12567039 0.10922138 0.12743570 0.08829063 0.11704342 0.08536120 0.13645681 0.10042195
[17] 0.24880845 0.16860369 0.22790244 0.17271791 0.15661511 0.19275500 0.19196326 0.22544634
[25] 0.09707505 0.21656858 0.16547388 0.12516108 0.09844085 0.23711611 0.07084277 0.16736313
[33] 0.07356731 0.16865990 0.13991114 0.22179775

[[2]][[1]]$yf
 [1] 0.2030008 0.3173118 0.2282571 0.1834186 0.3173118 0.2971464 0.1575632 0.3787852 0.1082135
[10] 0.1147236 0.1147236 0.1082135 0.1082135 0.1082135 0.1082135 0.1082135 0.2282571 0.2030008
[19] 0.2030008 0.1834186 0.1575632 0.1834186 0.1834186 0.2030008 0.1082135 0.2282571 0.2030008
[28] 0.1082135 0.1082135 0.2371161 0.1147236 0.1147236 0.1147236 0.2030008 0.1147236 0.2030008


[[2]][[2]]


[[3]]
[[3]][[1]]
[[3]][[1]]$x
 [1] 0.1568875 0.1725026 0.1703869 0.2279592 0.2005687 0.1908797 0.1812164 0.1429426 0.1614687
[10] 0.1792121 0.2154427 0.2359555 0.2102065 0.1645141 0.1308631 0.2506164 0.2169481 0.2526396
[19] 0.2580612 0.2496731 0.2400724 0.2143282 0.1626815 0.2016789 0.2354556 0.2063095 0.1888897
[28] 0.2131539 0.2534434 0.2537964 0.2192287 0.2486716 0.2604261 0.2585177 0.2358648 0.1542377

[[3]][[1]]$y
 [1] 0.05722627 0.17705910 0.11177962 0.15447008 0.18579931 0.16829387 0.14826053 0.10793710
 [9] 0.13445459 0.16788148 0.16788748 0.24158506 0.21069160 0.15872948 0.09819499 0.28412650
[17] 0.16229875 0.32890442 0.25743426 0.28894077 0.22271158 0.20661850 0.10286682 0.15284644
[25] 0.16305111 0.16997122 0.20130328 0.10645505 0.30261262 0.25777602 0.10387805 0.26588428
[33] 0.26828145 0.29619015 0.27357450 0.06820003

[[3]][[1]]$yf
 [1] 0.0828896 0.1644004 0.1352546 0.1656588 0.1656588 0.1656588 0.1644004 0.0828896 0.1186607
[10] 0.1644004 0.1656588 0.2459570 0.1656588 0.1352546 0.0828896 0.2855333 0.1656588 0.2855333
[19] 0.2855333 0.2855333 0.2459570 0.1656588 0.1186607 0.1656588 0.1656588 0.1656588 0.1656588
[28] 0.1656588 0.2855333 0.2855333 0.1656588 0.2658843 0.2855333 0.2855333 0.2459570 0.0828896


[[3]][[2]]


[[4]]
[[4]][[1]]
[[4]][[1]]$x
 [1] 0.1429239 0.1387844 0.2218590 0.1182296 0.1468817 0.1466908 0.3402315 0.2890817 0.1292108
[10] 0.1932092 0.1286691 0.1423629 0.1271427 0.3063619 0.2253164 0.2528256 0.1504117 0.1307400
[19] 0.1469667 0.3356008 0.2447417 0.2383977 0.2819196 0.2676795 0.3348372 0.3290096 0.1647244
[28] 0.1077739 0.3340839 0.2810676 0.1254004 0.3455767 0.2520377 0.2833718 0.2940115 0.4259479

[[4]][[1]]$y
 [1] 1.115306e-04 9.268979e-05 3.474377e-01 3.408479e-05 7.321045e-05 6.971079e-05
 [7] 3.476318e-01 3.474682e-01 6.580936e-05 3.473306e-01 7.746011e-05 1.093834e-04
[13] 9.546780e-05 3.476051e-01 3.473880e-01 3.473809e-01 6.885422e-05 5.060869e-05
[19] 1.201478e-04 3.476669e-01 3.473764e-01 3.474048e-01 3.474316e-01 3.473861e-01
[25] 3.476889e-01 3.476699e-01 6.965244e-05 5.850991e-05 3.476229e-01 3.474443e-01
[31] 1.280862e-04 3.476919e-01 3.474019e-01 3.475655e-01 3.474830e-01 6.021884e-01

[[4]][[1]]$yf
 [1] 8.939744e-05 8.939744e-05 3.473965e-01 4.629735e-05 8.939744e-05 8.939744e-05
 [7] 3.476625e-01 3.475056e-01 8.348643e-05 3.473306e-01 8.348643e-05 8.939744e-05
[13] 8.348643e-05 3.476051e-01 3.473965e-01 3.473965e-01 8.939744e-05 8.348643e-05
[19] 8.939744e-05 3.476625e-01 3.473965e-01 3.473965e-01 3.474379e-01 3.473965e-01
[25] 3.476625e-01 3.476464e-01 8.939744e-05 4.629735e-05 3.476464e-01 3.474379e-01
[31] 8.348643e-05 3.476919e-01 3.473965e-01 3.475056e-01 3.475056e-01 6.021884e-01


[[4]][[2]]

# analyze the mock feed pool
lapply(locs, bray_nmds_mock_feed, sodm_filtered_df = mock_feed_sodm_asvs_removed_dataframe, site = "MFP")
'csv_outputs/bray_dissimilar/mockfeeds' already existsExpected 4 pieces. Missing pieces filled with `NA` in 9 rows [1, 2, 3, 4, 5, 6, 7, 8, 9].
Run 0 stress 0.06364928 
Run 1 stress 0.09471005 
Run 2 stress 0.2265825 
Run 3 stress 0.06365546 
... Procrustes: rmse 0.002148102  max resid 0.004271723 
... Similar to previous best
Run 4 stress 0.0939424 
Run 5 stress 0.06365676 
... Procrustes: rmse 0.002442423  max resid 0.004857421 
... Similar to previous best
Run 6 stress 0.2222792 
Run 7 stress 0.06365594 
... Procrustes: rmse 0.005796783  max resid 0.01152563 
Run 8 stress 0.06365171 
... Procrustes: rmse 0.0009778457  max resid 0.001954567 
... Similar to previous best
Run 9 stress 0.06365912 
... Procrustes: rmse 0.002955246  max resid 0.005864934 
... Similar to previous best
Run 10 stress 0.06365587 
... Procrustes: rmse 0.002217254  max resid 0.004414995 
... Similar to previous best
Run 11 stress 0.09394542 
Run 12 stress 0.210603 
Run 13 stress 0.09548629 
Run 14 stress 0.2040939 
Run 15 stress 0.2222793 
Run 16 stress 0.09394843 
Run 17 stress 0.09464587 
Run 18 stress 0.09470022 
Run 19 stress 0.0947082 
Run 20 stress 0.06365309 
... Procrustes: rmse 0.001351187  max resid 0.002702174 
... Similar to previous best
*** Solution reached
Run 0 stress 0.1248886 
Run 1 stress 0.09366553 
... New best solution
... Procrustes: rmse 0.1997326  max resid 0.4466437 
Run 2 stress 0.2590489 
Run 3 stress 0.1443647 
Run 4 stress 0.1248886 
Run 5 stress 0.116627 
Run 6 stress 0.1248886 
Run 7 stress 0.1443647 
Run 8 stress 0.1166312 
Run 9 stress 0.09366558 
... Procrustes: rmse 0.0002539039  max resid 0.0004955897 
... Similar to previous best
Run 10 stress 0.146347 
Run 11 stress 0.1248886 
Run 12 stress 0.1166334 
Run 13 stress 0.160528 
Run 14 stress 0.116625 
Run 15 stress 0.1443647 
Run 16 stress 0.1166264 
Run 17 stress 0.1167294 
Run 18 stress 0.1166291 
Run 19 stress 0.0936655 
... New best solution
... Procrustes: rmse 6.323389e-05  max resid 0.0001308487 
... Similar to previous best
Run 20 stress 0.09366551 
... Procrustes: rmse 0.0001062808  max resid 0.0001854301 
... Similar to previous best
*** Solution reached

'csv_outputs/bray_dissimilar/mockfeeds' already existsExpected 4 pieces. Missing pieces filled with `NA` in 9 rows [1, 2, 3, 4, 5, 6, 7, 8, 9].
Run 0 stress 0.07183397 
Run 1 stress 0.07183397 
... Procrustes: rmse 7.598492e-06  max resid 1.485332e-05 
... Similar to previous best
Run 2 stress 0.1292396 
Run 3 stress 0.07183397 
... Procrustes: rmse 9.071516e-06  max resid 1.646231e-05 
... Similar to previous best
Run 4 stress 0.07183397 
... Procrustes: rmse 2.366477e-06  max resid 4.246065e-06 
... Similar to previous best
Run 5 stress 0.1292396 
Run 6 stress 0.1292398 
Run 7 stress 0.07183397 
... Procrustes: rmse 1.113012e-05  max resid 1.974735e-05 
... Similar to previous best
Run 8 stress 0.07183397 
... Procrustes: rmse 4.089457e-06  max resid 7.360054e-06 
... Similar to previous best
Run 9 stress 0.07183398 
... Procrustes: rmse 1.208527e-05  max resid 2.536354e-05 
... Similar to previous best
Run 10 stress 0.1292396 
Run 11 stress 0.07183397 
... Procrustes: rmse 3.958695e-06  max resid 7.239967e-06 
... Similar to previous best
Run 12 stress 0.07183397 
... Procrustes: rmse 6.767628e-06  max resid 1.107656e-05 
... Similar to previous best
Run 13 stress 0.07183397 
... Procrustes: rmse 6.732769e-06  max resid 1.143215e-05 
... Similar to previous best
Run 14 stress 0.07183397 
... Procrustes: rmse 2.185775e-06  max resid 4.154859e-06 
... Similar to previous best
Run 15 stress 0.07183397 
... Procrustes: rmse 1.171993e-06  max resid 2.293682e-06 
... Similar to previous best
Run 16 stress 0.07183397 
... New best solution
... Procrustes: rmse 1.10235e-06  max resid 2.079438e-06 
... Similar to previous best
Run 17 stress 0.1073256 
Run 18 stress 0.2250754 
Run 19 stress 0.1073257 
Run 20 stress 0.07183397 
... Procrustes: rmse 4.53578e-06  max resid 7.85255e-06 
... Similar to previous best
*** Solution reached

'csv_outputs/bray_dissimilar/mockfeeds' already existsExpected 4 pieces. Missing pieces filled with `NA` in 9 rows [1, 2, 3, 4, 5, 6, 7, 8, 9].
Run 0 stress 0.001975787 
Run 1 stress 0.003833382 
Run 2 stress 0.002294091 
... Procrustes: rmse 0.02957969  max resid 0.06563765 
Run 3 stress 0.002570182 
Run 4 stress 0.0003577373 
... New best solution
... Procrustes: rmse 0.02727485  max resid 0.04194552 
Run 5 stress 0.001907351 
Run 6 stress 0.0007806292 
... Procrustes: rmse 0.003996374  max resid 0.006402149 
... Similar to previous best
Run 7 stress 0.0003135241 
... New best solution
... Procrustes: rmse 0.0002299896  max resid 0.0004166386 
... Similar to previous best
Run 8 stress 0.3018151 
Run 9 stress 9.728205e-05 
... New best solution
... Procrustes: rmse 0.001534237  max resid 0.002814251 
... Similar to previous best
Run 10 stress 9.758163e-05 
... Procrustes: rmse 0.0002172372  max resid 0.0003445726 
... Similar to previous best
Run 11 stress 0.003105635 
Run 12 stress 0.000384661 
... Procrustes: rmse 0.001900999  max resid 0.003482793 
... Similar to previous best
Run 13 stress 9.675326e-05 
... New best solution
... Procrustes: rmse 0.0002157398  max resid 0.0003438748 
... Similar to previous best
Run 14 stress 0.004260075 
Run 15 stress 0.002718237 
Run 16 stress 0.001901804 
Run 17 stress 0.004203702 
Run 18 stress 0.00262929 
Run 19 stress 0.001750504 
Run 20 stress 0.0002349262 
... Procrustes: rmse 0.001101485  max resid 0.002134027 
... Similar to previous best
*** Solution reached
stress is (nearly) zero: you may have insufficient data

[[1]]
[[1]][[1]]
[[1]][[1]]$x
 [1] 0.12969477 0.10958570 0.11771040 0.09601389 0.09756598 0.13174901 0.11472929 0.11192856
 [9] 0.12277036 0.10408660 0.12633721 0.13398938 0.10489474 0.12217917 0.14687359 0.08830671
[17] 0.11286614 0.09693293 0.11473830 0.09698764 0.12180394 0.11331828 0.09577356 0.10010005
[25] 0.10735922 0.12472923 0.09867822 0.13710163 0.10325033 0.12304605 0.12711871 0.11815996
[33] 0.11682005 0.12845388 0.15710990 0.13305873

[[1]][[1]]$y
 [1] 0.11292424 0.04934745 0.06291186 0.02438304 0.04071540 0.11617164 0.06182837 0.04866942
 [9] 0.07178118 0.05985609 0.09957791 0.10116970 0.04911517 0.06541828 0.15378851 0.01393776
[17] 0.04999054 0.02987397 0.06683967 0.05176084 0.08271589 0.06086888 0.04147635 0.05336148
[25] 0.05351196 0.09612144 0.05544973 0.11285573 0.04056242 0.07267455 0.08791601 0.07479811
[33] 0.05652938 0.09313540 0.14441624 0.11001424

[[1]][[1]]$yf
 [1] 0.11006996 0.05174844 0.06291186 0.03191112 0.04623812 0.11006996 0.06173248 0.05174844
 [9] 0.07347760 0.05174844 0.09418769 0.11006996 0.05174844 0.07347760 0.14910237 0.01393776
[17] 0.05174844 0.03191112 0.06173248 0.04623812 0.07347760 0.06086888 0.03191112 0.04979121
[25] 0.05174844 0.09418769 0.04979121 0.11285573 0.04979121 0.07347760 0.09418769 0.07347760
[33] 0.06173248 0.09418769 0.14910237 0.11006996


[[1]][[2]]


[[2]]
[[2]][[1]]
[[2]][[1]]$x
 [1] 0.09486471 0.12097318 0.10099228 0.09409658 0.11593523 0.07340183 0.09927172 0.08903083
 [9] 0.10649828 0.10633260 0.10587594 0.11119368 0.09594250 0.10110508 0.08728567 0.08755330
[17] 0.09610044 0.09601493 0.11497171 0.11544096 0.09997613 0.09434976 0.09337393 0.10094043
[25] 0.10633563 0.08883171 0.11110650 0.08917919 0.09426727 0.08262075 0.10763045 0.09980406
[33] 0.10679740 0.08834883 0.07893388 0.08872040

[[2]][[1]]$y
 [1] 0.03149158 0.08483143 0.06457228 0.03954221 0.08896503 0.02039573 0.04863811 0.02830449
 [9] 0.06585594 0.05691991 0.04825077 0.08954277 0.04576129 0.07005559 0.03398557 0.03069606
[17] 0.06072833 0.05527719 0.08317187 0.08740105 0.06042096 0.03211008 0.03500635 0.05734267
[25] 0.05711761 0.03666610 0.04958664 0.02646602 0.02833983 0.01449590 0.07489700 0.06004582
[33] 0.06153742 0.02826155 0.02294621 0.03805146

[[2]][[1]]$yf
 [1] 0.03329801 0.08706584 0.05938323 0.03329801 0.08706584 0.01927928 0.05488121 0.03237202
 [9] 0.06296925 0.05938323 0.05938323 0.08635732 0.04576129 0.05938323 0.03098106 0.03098106
[17] 0.05488121 0.05488121 0.08635732 0.08706584 0.05926982 0.03329801 0.03329801 0.05926982
[25] 0.05938323 0.03237202 0.06296925 0.03237202 0.03329801 0.01927928 0.06296925 0.05926982
[33] 0.06296925 0.03098106 0.01927928 0.03237202


[[2]][[2]]


[[3]]
[[3]][[1]]
[[3]][[1]]$x
 [1] 0.07801445 0.07952722 0.09199279 0.09242663 0.10324405 0.05060173 0.09632989 0.12259860
 [9] 0.10755675 0.09044303 0.07068372 0.06981024 0.08297019 0.08423405 0.08594460 0.05229529
[17] 0.09509476 0.11504447 0.09231108 0.10967240 0.13449489 0.08383343 0.09845069 0.08790914
[25] 0.10072986 0.12808187 0.09863779 0.07245620 0.05435074 0.09011568 0.11549493 0.12276820
[33] 0.07693811 0.07929081 0.13089619 0.10626162

[[3]][[1]]$y
 [1] 0.08946311 0.06846987 0.07247073 0.06839914 0.14115901 0.01401325 0.08867140 0.16192811
 [9] 0.12166117 0.07900667 0.03880938 0.06023132 0.09077463 0.09219430 0.07760127 0.05140065
[17] 0.12082948 0.15043037 0.08227566 0.15529130 0.19907433 0.09182617 0.09920627 0.08469973
[25] 0.13950298 0.15374956 0.09890105 0.06419961 0.05495053 0.09560544 0.14581029 0.15048328
[33] 0.07864038 0.07665928 0.15952390 0.12360090

[[3]][[1]]$yf
 [1] 0.07830816 0.07830816 0.08348537 0.08348537 0.13148102 0.01401325 0.10190205 0.15538698
 [9] 0.13148102 0.08348537 0.05134797 0.05134797 0.08348537 0.08348537 0.08348537 0.05134797
[17] 0.10190205 0.15051065 0.08348537 0.15051065 0.19907433 0.08348537 0.10190205 0.08348537
[25] 0.13148102 0.15538698 0.10190205 0.06419961 0.05134797 0.08348537 0.15051065 0.15538698
[33] 0.07830816 0.07830816 0.15952390 0.13148102


[[3]][[2]]


[[4]]
[[4]][[1]]
[[4]][[1]]$x
 [1] 0.21565519 0.20559776 0.14253007 0.82105694 0.23074602 0.20483653 0.81896184 0.79134458
 [9] 0.09648571 0.15369417 0.91290869 0.15670174 0.22512511 0.91700536 0.88691019 0.11979673
[17] 0.87475314 0.12621099 0.19020092 0.88212332 0.85369718 0.81560429 0.14231421 0.16141021
[25] 0.81661512 0.80078055 0.86433000 0.75725644 0.11975569 0.23404484 0.25214280 0.86669936
[33] 0.83893795 0.77207372 0.73956678 0.28952762

[[4]][[1]]$y
 [1] 0.0007772069 0.0006471966 0.0004930579 1.4266836205 0.0009629720 0.0007346404
 [7] 1.4266844212 1.4261657898 0.0001657616 0.0005816072 1.4272819056 0.0004711314
[13] 0.0009490138 1.4272829564 1.4267642009 0.0004167141 1.4271168474 0.0004241873
[19] 0.0007898603 1.4271178905 1.4265991388 1.4267003072 0.0005242190 0.0003887358
[25] 1.4267013565 1.4261826018 1.4270343661 1.4263458865 0.0007196787 0.0006320038
[31] 0.0007305160 1.4270356191 1.4265167633 1.4263470163 1.4258282216 0.0006297504

[[4]][[1]]$yf
 [1] 0.0007772069 0.0007238991 0.0005024164 1.4266476013 0.0007808512 0.0007238991
 [7] 1.4266476013 1.4262603236 0.0001657616 0.0005024164 1.4272819056 0.0005024164
[13] 0.0007808512 1.4272829564 1.4270137848 0.0005024164 1.4270137848 0.0005024164
[19] 0.0007238991 1.4270137848 1.4266476013 1.4266476013 0.0005024164 0.0005024164
[25] 1.4266476013 1.4262603236 1.4270137848 1.4262603236 0.0005024164 0.0007808512
[31] 0.0007808512 1.4270137848 1.4266476013 1.4262603236 1.4258282216 0.0007808512


[[4]][[2]]

Crack open the bray dissimilarity files to take a look at anything > 0.49 dissimilar from the other replicates.

MFP: fishminiA - 36 entries - remove three replicates (see below)

F2_0 fishminiA - 6 entries (F2_0_1_3) F1_2 fishminiA - 8 entries (F1_2_2_3) F0_100 fishminiA - 18 entries F0_100 nsCOIFo - 6 entries (F0_100_1_1) F0_100 mifish - 18 entries F0_100 cep - 2 entries (F0_100_2_2 and F0_100_1_1) F1_0 fishminiA - 16 entries (F0_0_1_1 and F0_0_1_2)

I hate the idea of doing this manually, but for the time being, it is nice to have eyes on some of these data before dropping replicates.

Interesting to note that FishminiA has the highest incidence of dissimilarity issues.

Remove dissimilar replicates

# this is the dataframe that have been filtered by occupancy modeling and includes only those ASVs assigned to metazoan taxonomy
mock_feed_sodm_asvs_removed_dataframe
NA

A clean, non-redundant version of the reference sample dataframe

mockfeed_sodm_filtered_unique <- mock_feed_sodm_asvs_removed_dataframe %>% 
  select(locus, seq, sample, count) %>%
  unique() %>% # if there are multiple entries with different counts, we want to collapse those reads
  group_by(locus, seq, sample) %>%
  mutate(total_reads = sum(count)) %>%
  select(-count) %>%
  rename(count = total_reads)

So that is the dataframe from which we want to remove this particular list of locus-samples

# read in the list of samples to remove
mockfeed_tossers <- read_csv("../data/mock_feed_replicates_to_remove.csv")
Parsed with column specification:
cols(
  locus = col_character(),
  sample = col_character()
)

It turns out that an anti-join is all I need for this filtering step.

mockfeed_sodm_bray_filtered_unique <- mockfeed_sodm_filtered_unique %>%
  anti_join(., mockfeed_tossers, by = c("locus", "sample")) 

# remove the negative controls from this df
mockfeed_decontaminated <- mockfeed_sodm_bray_filtered_unique %>%
  filter(!str_detect(sample, "NEG") & !str_detect(sample, "M_A")) # remove positive controls too

Save that

saveRDS(mockfeed_decontaminated, "../data/mockfeed_decontaminated.rds", compress = "xz")

Okay, so that is the dataset that I can work through the assessment analyses with, beginning with summary statistics, then adding in the taxonomy and assessing proportion fishmeal and % reads, etc.

Taxonomy for those ASVs retained

# un-collapsed and collapsed versions of the taxonomy with a 98% identity threshold for species-level ID
tax_df_clean_slim <- readRDS("../data/uncollapsed_taxonomy_spp_98.rds")
clean_taxonomy_df_unique <- readRDS("../data/unique_taxonomy_spp_98.rds")

Adding back in the taxonomic information - uncollapsed, so there are multiple taxonomic entries for each locus/seq that need to be summarised.

# bind the complete (but filtered) taxonomic identities onto the ASV sequence information
mockfeed_taxonomy <- mockfeed_decontaminated %>%
  left_join(., tax_df_clean_slim, by = c("locus", "seq"))
  

Save that

# save output dataframe that has been filtered by Bray-Curtis as well as the occupancy modeling
saveRDS(mockfeed_taxonomy, "../data/mockfeed_taxonomy_sodm_bray_clean.rds", compress = "xz")
---
title: "Mock feed data - read in occupany modeling results and filter by Bray-Curtis"
output: html_notebook
---

The data decontamination includes two steps:
1. species occupancy detection modeling
2. Bray-Curtis dissimilarity analysis

Here, I'll read in the data from the SODM analysis, assess which ASVs will be removed based on that, and then move onto calculating the Bray-Curtis dissimilarities across sample replicates. Finally, the repicates that are more dissimilar (> 0.49) than similar to one another will be removed.


## Load data and libraries

```{r load-libraries}
library(tidyverse)
library(stringi)
library(vegan)
library(reshape2)
library(textshape)
library(rlist)

```

As I did with the reference mock communities, the way I'm thinking about this is to create a .txt file with a list of the file names and loci and to read that in, but ideally, I would also have a column for the sample name so that I could actually properly filter for each locus-sample when anti-joining with the dataframe.

Before getting into all of that regex stuff, probably best to take a quick look at whether there are many ASVs that get removed for the data from F1 or the mock feed pools.

```{r load-dataframes}
# Full dataframe
features_w_taxonomy <- readRDS("../data/feature_df_no_eDNA_metazoa_only.rds")

# and newly updated, the same dataframes, but using a 98% identity threshold for any species-level assignments
tax_df_spp_98 <- readRDS("../data/uncollapsed_taxonomy_spp_98.rds")
unique_tax_spp_98 <- readRDS("../data/unique_taxonomy_spp_98.rds")


# meta data for group and type assignments
meta <- read_csv("../data/jan_sample_list.csv")

# use the new name column to bind to the input file
feature_tax_name_revised <- features_w_taxonomy %>%
  left_join(., meta, by = "sample") %>%
  select(locus, seq, new_name, count) %>%
  rename(sample = new_name)


```


## Occupancy modeling data

Based on the SODM filtering, now I need to read those data back in for the mock feed data/mixtures and pools.

The files are located in this directory:
/Users/dianabaetscher/Documents/git-repos/metabarcoding-methods/Rmd_fixed_db/csv_outputs/SODM


```{r create-dataframe-from-csvs}
# get the names of the files
fdf <- read.table("~/Documents/git-repos/metabarcoding-methods/data/sodm_samples_loc.txt", stringsAsFactors = FALSE, header = TRUE) %>%
  tbl_df()
dir <- "~/Documents/git-repos/metabarcoding-methods/Rmd_fixed_db/csv_outputs/SODM"

# cycle over them, read them and add the locus column on each.
# at the end, bind them together.
mock_feed_sodm_df <- lapply(1:nrow(fdf), function(i) {
  read_csv(paste(dir, fdf$file[i], sep = "/"), col_names = TRUE) %>%
    mutate(locus = fdf$locus[i]) %>%
    mutate(sample = fdf$sample[i]) %>%
    select(locus, sample, everything())
}) %>%
  bind_rows() %>%
  group_by(locus, sample, seq) %>%
  mutate(max_estimate = sum(estimate,std.error)) %>%
  mutate(max_estimate = ifelse(max_estimate > 1, 1, max_estimate)) %>% # make 1 the maximum probability.
  select(locus, seq, estimate, std.error, max_estimate)

```


So these are the ASVs that I would be filtering
```{r filter-asvs-by-sodm}
mock_feed_sodm_asvs_removed <- mock_feed_sodm_df %>%
  filter(max_estimate < 0.8)

mock_feed_sodm_asvs_removed
```
There aren't very many of these, but some...

so for consistency sake, I suppose better to remove them.


Anti-join the ASVs to remove with the full dataframe
```{r}
mock_feed_feature_df <- feature_tax_name_revised %>%
  filter(!str_detect(sample, "VRP") & !str_detect(sample, "FRP") & !str_detect(sample, "extr_blank")) %>%
  separate(sample, into = c("filler", "perc_fishmeal", "extract", "pcr_rep"), sep = "_", remove = FALSE) %>%
  unite(feed, filler, perc_fishmeal, sep = "_", remove = TRUE) %>%
  select(-extract, -pcr_rep) %>%
  mutate(feed = ifelse(str_detect(feed, "MFP"), "MFP", feed)) %>%
  mutate(feed = ifelse(str_detect(feed, "MEP"), "MEP", feed))

# check that all of those modifications took effect - basically to make a column that I can use for an anti-join with the SODM filtered data
mock_feed_feature_df %>%
  filter(str_detect(sample, "MFP"))
```

Use an anti-join to remove the 27 ASVs from the full feature table.
```{r}
mock_feed_sodm_asvs_removed_dataframe <- mock_feed_feature_df %>%
  anti_join(., mock_feed_sodm_asvs_removed, by = c("locus", "seq", "feed" = "sample")) %>%
  select(-feed) # remove the column that I used for the join since I don't need it moving forward

```

Save the output
```{r save-output-rds}
saveRDS(mock_feed_sodm_asvs_removed_dataframe, "../data/mockfeed_sodm_asvs_removed_feature_df.rds", compress = "xz")

```



## Dissimilarity analyses


Using the dataframe generated above...

Dissimilarity analyses include a PERMANOVA on Bray-Curtis
Jaccard similarities (minimizing the effect of PCR amplification bias)


The process for looking at the dissimilarity among replicates is to:
1. read in data that has been cleaned up using the occupancy modeling
2. create a community matrix (per locus)
3. standardize data across replicates (fct decostand)
4. generate Bray-Curtis distances (fct vegdist)
   4a. Are any replicates more dissimilar than similar? 
5. generate NMDS plots from distance matrix (fct metaMDS)



Outcomes:
Based on the NMDS plots and Bray-Curtis dissimilarity index, I will generate a list of samples to remove.


```{r load-functions}
source("../R/metabarcoding-funcs.R")
```


Cycle over a list of the loci
```{r locus-list}
# grab the names of the loci from the full dataframe
locs <- c("cep", "mifish", "nsCOIFo", "fishminiA")

# how many feed samples?
mock_feed_sodm_asvs_removed_dataframe %>%
  select(sample) %>%
  unique()

```

NOTE: MEP and MFP have a diff number of parts than the mock feeds... 9 replicates vs. 6 replicates,
so splitting the sample into reference, pool, and pcr replicate will look different.


## Bray-Curtis function

Output from the function should go into a directory called
`csv_outputs/bray_dissimilar/mockfeeds/`

If this directory doesn't exist, the function will create it.
```{r}
bray_nmds_mock_feed(mock_feed_sodm_asvs_removed_dataframe, loc = "cep", site = "F1_0")

```

```{r 100%-fishmeal-feed}
# analyze the four loci for mock feed sample F0_100
lapply(locs, bray_nmds_mock_feed, sodm_filtered_df = mock_feed_sodm_asvs_removed_dataframe, site = "F0_100")
```

#### Filler 1

```{r 0%-fishmeal-filler1}
# lapply the function with all four loci
lapply(locs, bray_nmds_mock_feed, sodm_filtered_df = mock_feed_sodm_asvs_removed_dataframe, site = "F1_0")

```

```{r 10%-fishmeal-filler1}
# analyze sample F1_10
lapply(locs, bray_nmds_mock_feed, sodm_filtered_df = mock_feed_sodm_asvs_removed_dataframe, site = "F1_10")

```

```{r 2%-fishmeal-filler1}
# analyze sample F1_2
lapply(locs, bray_nmds_mock_feed, sodm_filtered_df = mock_feed_sodm_asvs_removed_dataframe, site = "F1_2_")

```


```{r 25%-fishmeal-filler1}
# analyze sample F1_25
lapply(locs, bray_nmds_mock_feed, sodm_filtered_df = mock_feed_sodm_asvs_removed_dataframe, site = "F1_25")

```


#### Filler 2

```{r 25%-fishmeal-filler2}
# analyze sample F2_25
lapply(locs, bray_nmds_mock_feed, sodm_filtered_df = mock_feed_sodm_asvs_removed_dataframe, site = "F2_25")

```

```{r 0%-fishmeal-filler2}
# analyze sample F2_0
lapply(locs, bray_nmds_mock_feed, sodm_filtered_df = mock_feed_sodm_asvs_removed_dataframe, site = "F2_0")

```



## Mock feed pools


```{r mock-equal-pool}
# analyze the mock equal pool samples
lapply(locs, bray_nmds_mock_feed, sodm_filtered_df = mock_feed_sodm_asvs_removed_dataframe, site = "MEP")

```

```{r mock-feed-pool}
# analyze the mock feed pool
lapply(locs, bray_nmds_mock_feed, sodm_filtered_df = mock_feed_sodm_asvs_removed_dataframe, site = "MFP")

```

Crack open the bray dissimilarity files to take a look at anything > 0.49 dissimilar from the other replicates.

MFP: fishminiA - 36 entries - remove three replicates (see below)

F2_0 fishminiA - 6 entries (F2_0_1_3)
F1_2 fishminiA - 8 entries (F1_2_2_3)
F0_100 fishminiA - 18 entries
F0_100 nsCOIFo - 6 entries (F0_100_1_1)
F0_100 mifish - 18 entries
F0_100 cep - 2 entries (F0_100_2_2 and F0_100_1_1)
F1_0 fishminiA - 16 entries (F0_0_1_1 and F0_0_1_2)


I hate the idea of doing this manually, but for the time being, it is nice to have eyes on some of these data before dropping replicates.

Interesting to note that FishminiA has the highest incidence of dissimilarity issues.


## Remove dissimilar replicates

```{r load-data}
# this is the dataframe that have been filtered by occupancy modeling and includes only those ASVs assigned to metazoan taxonomy
mock_feed_sodm_asvs_removed_dataframe

```


A clean, non-redundant version of the reference sample dataframe
```{r}
mockfeed_sodm_filtered_unique <- mock_feed_sodm_asvs_removed_dataframe %>% 
  select(locus, seq, sample, count) %>%
  unique() %>% # if there are multiple entries with different counts, we want to collapse those reads
  group_by(locus, seq, sample) %>%
  mutate(total_reads = sum(count)) %>%
  select(-count) %>%
  rename(count = total_reads)

```

So that is the dataframe from which we want to remove this particular list of locus-samples
```{r}
# read in the list of samples to remove
mockfeed_tossers <- read_csv("../data/mock_feed_replicates_to_remove.csv")

```

It turns out that an anti-join is all I need for this filtering step.
```{r}
mockfeed_sodm_bray_filtered_unique <- mockfeed_sodm_filtered_unique %>%
  anti_join(., mockfeed_tossers, by = c("locus", "sample")) 

# remove the negative controls from this df
mockfeed_decontaminated <- mockfeed_sodm_bray_filtered_unique %>%
  filter(!str_detect(sample, "NEG") & !str_detect(sample, "M_A")) # remove positive controls too
```

Save that
```{r save-decontaminated-df}
saveRDS(mockfeed_decontaminated, "../data/mockfeed_decontaminated.rds", compress = "xz")
```

Okay, so that is the dataset that I can work through the assessment analyses with, beginning with summary statistics, then adding in the taxonomy and assessing proportion fishmeal and % reads, etc.



### Taxonomy for those ASVs retained

```{r load-taxonomic-dfs}
# un-collapsed and collapsed versions of the taxonomy with a 98% identity threshold for species-level ID
tax_df_clean_slim <- readRDS("../data/uncollapsed_taxonomy_spp_98.rds")
clean_taxonomy_df_unique <- readRDS("../data/unique_taxonomy_spp_98.rds")

```

Adding back in the taxonomic information - uncollapsed, so there are multiple taxonomic entries for each locus/seq that need to be summarised.

```{r add-taxonomy}
# bind the complete (but filtered) taxonomic identities onto the ASV sequence information
mockfeed_taxonomy <- mockfeed_decontaminated %>%
  left_join(., tax_df_clean_slim, by = c("locus", "seq"))
  
```

Save that
```{r save-output}
# save output dataframe that has been filtered by Bray-Curtis as well as the occupancy modeling
saveRDS(mockfeed_taxonomy, "../data/mockfeed_taxonomy_sodm_bray_clean.rds", compress = "xz")

```
